http://hlt.suda.edu.cn/api.php?action=feedcontributions&feedformat=atom&user=Xjshi 2026-09-21T03:40:42Z 用户贡献 MediaWiki 1.35.2 http://hlt.suda.edu.cn/index.php?title=Members&diff=5862 2025-02-26T14:04:58Z

<p>Xjshi：</p> <hr /> <div><br /> == 在校老师 ==<br /> * [[Faculty|English Version]]<br /> * 教师：[https://zhangminsuda.github.io/ 张民]、[[Wenliang|陈文亮]]、[http://hlt.suda.edu.cn/index.php/%E6%AE%B5%E6%B9%98%E7%85%9C 段湘煜]、[https://web.suda.edu.cn/zhli13 李正华]、[http://web.suda.edu.cn/zhouxiabing/ 周夏冰]、龚晨<br /> * 科研助理：[[仇慧敏]]<br /> <br /> == 在校学生（[http://hlt.suda.edu.cn/index.php/Stu_candidates 招生说明]）==<br /> <br /> * 2019博：贾昊、余南 (2)<br /> <br /> * 2020博：刘振华、梁晓波、张建新、刘亚慧 (4)<br /> <br /> * 2021博：[https://spico197.github.io 朱桐]、[http://cv.hqzhou.com/ 周厚全]、张宇（3）<br /> <br /> * 2022博：侯洋、周仕林（2）<br /> <br /> * 2023博：谈川源<br /> <br /> * 2024博：季佰军<br /> <br /> <br /> <br /> * 2021硕：谈川源（转博）、章岳、黄赛豪、窦晨晖、严福康、崔秀莲、张磊、周烁、张竹君、董川奇、周文杰、缪思睿、杨帆、王泽、高晓倩 （15）<br /> <br /> * 2022硕：汤添文、吴孟松、邵文彪、辜仰淦、蒋浩辰、刘雨萌、马溪、胡宫朕、姚煜铖、王凯悦、张誉泷、李博、张婉群（13）<br /> <br /> * 2023硕：韩翰、张翔、熊浩、乔子恒、王学彬、张紫岩、陈杰琳、鞠鑫、冯俊皓、曹蕊、李扬韬、杜天译 （12）<br /> <br /> * 2024硕：韩泰来、潘豪、周昊喆、陈苏金、周志、王康、周梓轩<br /> <br /> == 访问学者/学生==<br /> * 访问学者：秦彦霞（东华大学讲师，哈工大博士）<br /> * 访问学生：杨明明（哈工大博士生）<br /> <br /> == 毕业学生(毕业第一次工作去向) ==<br /> <br /> === 博士 ===<br /> * 2024毕业博：郁俊杰（苏州城市学院） <br /> <br /> * 2022毕业博：[http://hlt.suda.edu.cn/gongchen/ 龚晨]（苏州大学）、[http://hlt.suda.edu.cn/kiro 夏庆荣]（华为）、[[李英]]（昆明理工大学）、李亚超（西北民族大学）、宋楷（字节跳动）<br /> <br /> * 2018毕业博：王星（腾讯AILab）<br /> <br /> === 硕士 ===<br /> <br /> * 2024年毕业硕（2021硕）：谈川源（转博）、任俊飞（美团）、余子健（美团）、项健翔（B站）、刘资蕴（百度）、崔秀莲、窦晨晖（公务员）、黄赛豪（得物）、严福康（小米）、张磊（科沃斯）、章岳（字节）（11）<br /> * 2023年毕业硕（2020硕）：张智林（美团）、张国梁（OPPO）、陈跃鹤（蚂蚁）、张飞宇（百度）、周沛（南京银行）、侯洋（转博）、周仕林（转博）、李嘉诚（中国移动研究院西安）、李帅克（创业）、李扬（中国移动研究院苏州）、刘泽洋（公务员）、张金鹏、金畅、肖妮妮、段仁翀、张冕(出国读博）、丁家杰 （17）<br /> <br /> * 2022毕业硕：贾永辉（字节）、[https://spico197.github.io/ 朱桐]（转博）、刘振华（转博）、杨浩苹（思必驰）、周厚全（转博）、周明月、贾浩（腾讯）、章华奥（同花顺）、王煦（智慧芽）、吴世龙、邱石贵（百度）、张世奇（VIVO）、陈楠（工行）、陈晨（美团）、李子仪（交行）（16）<br /> <br /> * 2021毕业硕：方晔玮（百度）、王海涛（华为）、马进（美团）、张鹏举（腾讯）、王铭涛（苏大）、蒋炜（华为）、刘亚慧（苏大转博）、陆凯华（上海银行）、吴锟（百度）、张宇（苏大转博）、季佰军（腾讯）、史小静（搜狗）、宁秋怡（联通）、肖康(网易)（14）<br /> <br /> * 2020毕业硕：张栋（同花顺）、杨一帆（思必驰）、朱宗奎（华为）、周俊佐（阿里巴巴）、郁圣卫、黄德朋（小红书）、彭雪（移动苏州）、章波（阿里巴巴）、谭敏（华为）、周孝青（OPPO）、殷明明（搜狗）、俞鸿飞（美团） (13)<br /> <br /> * 2019毕业硕：何正球（美团）、杨耀晟（阿里巴巴）、郭丽娟（狗尾草）、孙佳伟（苏州微软）、朱运（搜狗）、汪琪（深圳招商银行总行）、王坤（杭州搜狗研究院）、龚晨（苏大读博）、夏庆荣（苏大读博） (9)<br /> <br /> * 2018毕业硕：陈伟（爱奇艺）、凡子威（搜狗）、卢奇（美团）、张月（阿里巴巴） (4)<br /> <br /> * 2017毕业硕：巢佳媛（阿里巴巴）、陈志鹏（百度公司）、龚慧敏（同程公司）、郁俊杰（苏大读博）(4)<br /> <br /> * 2016毕业硕：马春平（阿里巴巴）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Papers&diff=5418 2024-03-11T04:22:35Z

<p>Xjshi：/* 2022 */</p> <hr /> <div>文章(格式见页尾)包括：<br /> * xACL(ACL/NAACL/EACL/AACL) EMNLP IJCAI AAAI COLING IJCNLP NLPCC<br /> * CCF-A/B Journal/Conference<br /> * SCI Journal<br /> * 软件学报/计算机学报/中国科学<br /> <br /> == [http://hlt.suda.edu.cn/index.php/Papers-details 论文摘要等信息] ==<br /> <br /> == 最新录用 ==<br /> <br /> * Jianxiang Xiang, Zhenhua Liu, Haodong Liu, Yin Bai, Jia Cheng and Wenliang Chen. DiffusionDialog: Diverse Dialog Generation Model with Diffusion in Latent Space. LREC-COLING-2024.<br /> * Tianwen Tang, Tong Zhu, Haodong Liu, Yin Bai, Jia Cheng and Wenliang Chen. MPPE-DST: Mixture of Prefix Prompt Experts for LLM in Zero-Shot Dialogue State Tracking. LREC-COLING-2024.<br /> * Junjie Yu, Xing Wang, and Wenliang Chen. Reliable Data Generation and Selection for Low-Resource Relation Extraction. AAAI-2024.<br /> <br /> * Chuanqi Dong, Wenjie Zhou, Xiangyu Duan, Yuqi Zhang and Min Zhang: Multimodal Cross-lingual Phrase Retrieval, COLING 2024.<br /> * Baijun Ji, Xiangyu Duan, Zhenyu Qiu, Tong Zhang, Junhui Li, Hao Yang and Min Zhang: Submodular-based In-context Example Selection for LLMs-based Machine Translation, COLING 2024.<br /> * Wenjie Zhou, Qiang Wang, Mingzhou Xu, MING CHEN and Xiangyu Duan: Revisiting the Self-Consistency Challenges in Multi-Choice Question Formats for Large Language Model Evaluation, Short Paper, COLING 2024.<br /> <br /> == 2023 ==<br /> <br /> * Tong Zhu, Junfei Ren, Zijian Yu, Mengsong Wu, Guoliang Zhang, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Min Zhang. Mirror: A Universal Framework for Various Information Extraction Tasks. The 2023 Conference on Empirical Methods in Natural Language Processing. 2023.<br /> * Tong Zhu, Guoliang Zhang, Zechang Li, Zijian Yu, Junfei Ren, Mengsong Wu, Zhefeng Wang, Baoxing Huai, Pingfu Chao, Wenliang Chen. CED: Catalog Extraction from Documents. The 17th International Conference on Document Analysis and Recognition. 2023.<br /> * Mian Zhang, Xiabing Zhou, Wenliang Chen, Min Zhang. Emotion Recognition in Coversation from Variable-lenght Context. ICASSP 2023.<br /> * Houquan Zhou, Yumeng Liu, Zhenghua Li*, Min Zhang, Bo Zhang, Chen Li, Ji Zhang, Fei Huang. 2023. Improving Seq2Seq Grammatical Error Correction via Decoding Interventions. Findings of '''EMNLP''', pages 7393–7405. [https://arxiv.org/abs/2310.14534 arxiv][https://github.com/Jacob-Zhou/gecdi code][https://www.semanticscholar.org/paper/Improving-Seq2Seq-Grammatical-Error-Correction-via-Zhou-Liu/4711f26c0295fed15161b6145800b3df1ab9c0f6 citation]<br /> * Yue Zhang, Leyang Cui, Enbo Zhao, Wei Bi, Shuming Shi. 2023. RobustGEC: Robust Grammatical Error Correction Against Subtle Context Perturbation. EMNLP 2023.[https://arxiv.org/pdf/2310.07299.pdf arxiv] [https://github.com/hillzhang1999/RobustGEC code]<br /> * Saihao Huang, Lijie Wang, Zhenghua Li*, Zeyang Liu, Chenhui Dou, Fukang Yan, Xinyan Xiao, Hua Wu, and Min Zhang. 2023. SeSQL: A High-Quality Large-Scale Session-Level Chinese Text-to-SQL Dataset. NLPCC 2023, pages 537-550.[[文件:SeSQL_A_High-Quality_Large-Scale_Session-Level_Chinese_Text-to-SQL_Dataset.pdf]] [https://arxiv.org/abs/2208.12711 arxiv]<br /> * Yue Zhang, Bo Zhang, Haochen Jiang, Zhenghua Li*, Chen Li, Fei Huang, Min Zhang. 2023. NaSGEC: Multi-Domain Chinese Grammatical Error Correction for Native Speaker Texts. Findings of ACL 2023. pp 9935-9951. [https://aclanthology.org/2023.findings-acl.630.pdf official] [https://arxiv.org/pdf/2305.16023.pdf arxiv] [https://github.com/HillZhang1999/NaSGEC code]<br /> * Jinpeng Zhang, Nini Xiao, Ke Wang, Chuanqi Dong, Xiangyu Duan*, Yuqi Zhang, Min Zhang: Disambiguated Lexically Constrained Neural Machine Translation, ACL 2023 Findings.<br /> <br /> == 2022 ==<br /> <br /> <br /> * Yahui Liu, Haoping Yang, Chen Gong*, Qingrong Xia, Zhenghua Li, Min Zhang. 2022. MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset. In '''NAACL'''. [http://arxiv.org/abs/2205.06703 arxiv]<br /> * Yue Zhang, Zhenghua Li*, Zuyi Bao, Jiacheng Li, Bo Zhang, Chen Li, Fei Huang, Min Zhang. 2022. MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction. In '''NAACL'''. [https://arxiv.org/abs/2204.10994 arxiv]<br /> * Ying Li, Shuaike Li, Min Zhang. 2022. Semi-supervised Domain Adaptation for Dependency Parsing with Dynamic Matching Network. In '''ACL 2022'', pages 1035--1045. [https://aclanthology.org/2022.acl-long.74.pdf official-pdf] [http://hlt.suda.edu.cn/index.php/%E6%96%87%E4%BB%B6:Liying_ACL2022_camera_ready.pdf camera ready pdf] [https://underline.io/lecture/52551-long-semi-supervised-domain-adaptation-for-dependency-parsing-with-dynamic-matching-network video].<br /> * Houquan Zhou, Yang Li, Zhenghua Li, and Min Zhang. 2022. Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging. In Findings of the Association for Computational Linguistics: ACL 2022, pages 3276–3290, Dublin, Ireland. Association for Computational Linguistics. [http://hlt.suda.edu.cn/LA/papers/acl-findings-hqzhou-bridging.pdf pdf] [https://arxiv.org/pdf/2203.10315 camera ready pdf] [https://aclanthology.org/2022.findings-acl.259.pdf offcial pdf] [https://underline.io/lecture/49965-findings-bridging-pre-trained-language-models-and-hand-crafted-features-for-unsupervised-pos-tagging video]<br /> * Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Yuan, Min Zhang. Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph. IJCAI. 2022<br /> * Chang Jin, Shigui Qiu, Nini Xiao, Hao Jia. AdMix: A Mixed Sample Data Augmentation Method for Neural Machine Translation. IJCAI. 2022<br /> * Xiabing Zhou, Renjie Feng, Xiaotong Jiang, and ZhongqingWang. Exploring Logographic Image for Chinese Aspect-based Sentiment. EMNLP(findings),2022<br /> * Jinpeng Zhang, Chuanqi Dong, Xiangyu Duan*, Yuqi Zhang, Min Zhang: Third-Party Aligner for Neural Word Alignments, EMNLP 2022 Findings.<br /> * Xin Ge, Ke Wang, Jiayi Wang, Nini Xiao, Xiangyu Duan, Yu Zhao, Yuqi Zhang: TSMind: Alibaba and Soochow University’s Submission to the WMT22 Translation Suggestion Task, WMT 2022.<br /> <br /> == 2021 ==<br /> <br /> * Yang Hou, Houquan Zhou, Zhenghua Li*, Yu Zhang, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. A Coarse-to-Fine Labeling Framework for Joint Word Segmentation, POS Tagging, and Constituent Parsing. Proceedings of CoNLL-2021, pp. 290–299. Punta Cana, Dominican Republic (Online), 10-11 Nov. 2021. [[文件:CoNLL_2021_yhou_official_version.pdf]]<br /> <br /> * Kun Wu, Lijie Wang, Zhenghua Li, Ao Zhang, Xinyan Xiao, Hua Wu, Min Zhang, Haifeng Wang. Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-Domain Text-to-SQL Parsing. Proceedings of EMNLP-2021, pp. 8974--8983. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP2021_camera_ready_Data_Augmentation_with_Hierarchical_SQL_to_Question_Generation_forCross_domain_Text_to_SQL_Parsing-09101500.pdf ‎]]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Rui Wang, Min Zhang. Stacked AMR Parsing with Silver Data. Proceedings of EMNLP-2021 Findings, pp. 4729--4738. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_Stacked_AMR_Parsing_with_Silver_Data.pdf]]<br /> <br /> * Ying Li, Meishan Zhang, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. APGN: Adversarial and Parameter Generation Networks for Multi-Source Cross-Domain Dependency Parsing. Proceedings of EMNLP-2021 Findings, pp. 1727–1733. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_yli_camera_ready.pdf]]<br /> <br /> * Chen Gong, Saihao Huang, Houquan Zhou, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. An In-depth Study on Internal Structure of Chinese Words. Proceedings of ACL-2021, pp. 5823–5833. Online, Virtual Event, 1-6 Aug. 2021. [[文件:2021.acl-long.452.pdf]]<br /> <br /> * Qingrong Xia, Bo Zhang, Rui Wang, Zhenghua Li*, Yue Zhang, Fei Huang, Luo Si, Min Zhang. 2021. A Unified Span-Based Approach for Opinion Mining with Syntactic Constituents. Proceedings of NAACL-2021, pp. 1795-1804. Mexico City, Mexico (Online), 6-11 June. 2021. [[文件:2021.naacl-main.144.pdf]]<br /> <br /> * Jinpeng Zhang, Baijun Ji, Nini Xiao, Xiangyu Duan*, Min Zhang, Yangbin Shi, Weihua Luo: Combining Static Word Embeddings and Contextual Representations for Bilingual Lexicon Induction, ACL 2021 Findings. [https://aclanthology.org/2021.findings-acl.260.pdf anthology]<br /> <br /> == 2020 == <br /> <br /> * Zhengqiu HE, Wenliang CHEN, Yuyi WANG, Wei ZHANG, Gaochun WANG, Min ZHANG. Improving Neural Relation Extraction with Positive and Unlabeled Learning. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), pp. 7927-7934. New York, 7-12 Feb. 2020，<br /> <br /> * 杨一帆, 马进, 王海涛, 何正球，陈文亮，张民. 基于简介文本的中文人物关系图谱属性补全与纠错. 中国科学-信息科学. V50(7) : 1003-1018(2020)<br /> <br /> * Junjie Yu, Tong Zhu, Wenliang Chen, Wei Zhang and Min Zhang. Improving Relation Extraction with Relational Paraphrase Sentences. COLING2020, pp. 1687-1698. Online, Dec. 2020[http://hlt.suda.edu.cn/images/9/96/Coling2020-junjie2073_Paper.pdf pdf]<br /> <br /> * Tong Zhu, Haitao Wang, Junjie Yu, Xiabing Zhou, Wenliang Chen, Wei Zhang and Min Zhang. Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction. COLING2020. pp. 6436-6447, Online, Dec. 2020 [https://arxiv.org/pdf/2010.16275.pdf pdf], [https://github.com/Spico197/NYT-H 数据下载@github]<br /> <br /> * Baijun JI, Zhirui ZHANG, Xiangyu DUAN, Min ZHANG, Boxing CHEN and Weihua LUO. Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Xiangyu Duan, Baijun Ji, Hao Jia, Min Tan, Min Zhang, Boxing Chen, Weihua Luo, Yue Zhang: Bilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences. The 58th Annual Meeting of the Association for Computational Linguistics (ACL-2020).<br /> <br /> * Kai SONG, Kun WANG, Heng YU, Yue ZHANG, Zhongqiang HUANG, Weihua LUO, Xiangyu DUAN and Min ZHANG. Alignment-Enhanced Transformer for Constraining NMT with Pre-Specified Translations. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Kai Song, Xiaoqing Zhou, Heng Yu, Zhongqiang Huang, Yue Zhang, Weihua Luo, Xiangyu Duan, Min Zhang: Towards Better Word Alignment in Transformer. IEEE ACM Transaction Audio Speech Language Processing (TASLP), 2020.<br /> <br /> * Huaao Zhang,Shigui Qiu, Xiangyu Duan*,Min Zhang: Token Drop mechanism for Neural Machine Translation. The International Conference on Computational Linguistics (Coling-2020) (short paper).<br /> <br /> * Chen Gong, Zhenghua Li, Qingrong Xia, Wenliang Chen and Min Zhang. Hierarchical LSTM with char-subword-word tree-structure representation for Chinese named entity recognition. Science China Information Science, 2020, 63(10):1-15. [[文件:Hierarchical_LSTM_with_char-subword-word_tree-structure_representation_for_Chinese_named_entity_recognition.pdf]]<br /> <br /> * Ying Li, Zhenghua Li* and Min Zhang. Semi-supervised Domain Adaptation for Dependency Parsing via Improved Contextualized Word Representations. Proceedings of COLING-2020. pp. 3806–3817. Barcelona, Spain (Online), 8-13 Dec. 2020.[https://www.aclweb.org/anthology/2020.coling-main.338.pdf pdf] [[文件:Liying-2020.coling-main.338.pdf]]<br /> <br /> * Qingrong Xia, Rui Wang, Zhenghua Li, Yue Zhang and Min Zhang*. Semantic Role Labeling with Heterogeneous Syntactic Knowledge. Proceedings of COLING-2020. pp. 2979-2990. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/2020.coling-main.266.pdf pdf][[文件:Xiaqingrong-2020.coling-main.266.pdf]]<br /> <br /> * Chen Gong, Zhenghua Li*, Bowei Zou and Min Zhang. Multi-grained Chinese Word Segmentation with Weakly Labeled Data. Proceedings of COLING-2020. pp. 2026–2036. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/D17-1072.pdf pdf][[文件:Gongchen-2020.coling-main.183.pdf]]<br /> <br /> * Lijie Wang, Ao Zhang, Kun Wu, Ke Sun, Zhenghua Li, Hua Wu*, Min Zhang and Haifeng Wang. DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset. Proceedings of EMNLP-2020. pp. 6923-6935. Online, 16-20 Nov. 2020. [https://www.aclweb.org/anthology/2020.emnlp-main.562.pdf pdf][[文件:2020.emnlp-main.562.pdf]]<br /> <br /> * Houquan Zhou, Yu Zhang, Zhenghua Li, and Min Zhang. Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing? Proceedings of NLPCC-2020, pp. 179--191. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo.pdf pdf]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official-w-content.pdf pdf-official-w-content]) &lt;font color=&quot;#FF0000&quot;&gt;&lt;b&gt;(best paper!)&lt;/b&gt;&lt;/font&gt; <br /> <br /> * Yu Zhao, Mingyue Zhou, Zhenghua Li, and Min Zhang. Dependency Parsing with Noisy Multi-Annotation Data. Proceedings of NLPCC-2020, pp. 120-131. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/images/e/e5/212_Final_Manuscript_%281%29.pdf pdf]）([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official-w-content.pdf pdf-official-w-content])<br /> <br /> * Yu Zhang, Houquan Zhou, Zhenghua Li. 2020. Fast and Accurate Neural CRF Constituency Parsing. Proceedings of IJCAI-2020, pp. 4046-4053. Yokohama, Japan, 11-17 Jul. 2020. [https://www.ijcai.org/Proceedings/2020/0560.pdf pdf-official] [http://hlt.suda.edu.cn/LA/papers/0560.pdf pdf] [[http://hlt.suda.edu.cn/LA/videos/V5.mp4 video(5 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V10.mp4 video(10 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V15.mp4 video(15 min version)]]<br /> <br /> * Yu Zhang, Zhenghua Li, Min Zhang. 2020. Efficient Second-Order TreeCRF for Neural Dependency Parsing. Proceedings of ACL-2020, pp. 3295-3305. Seattle, America, 5-10 Jul. 2020. ][https://www.aclweb.org/anthology/2020.acl-main.302.pdf pdf-official]] [[http://hlt.suda.edu.cn/LA/papers/2020.acl-main.302.pdf pdf]] [[http://hlt.suda.edu.cn/LA/videos/2020-12-28%2022-21-45.mp4 video]]<br /> <br /> * Bo Zhang, Yue Zhang, Rui Wang, Zhenghua Li, Min Zhang. Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks. Proceedings of ACL-2020, pp. 3249-3258. Seattle, America, 5-10 Jul. 2020. [https://www.aclweb.org/anthology/2020.acl-main.297.pdf pdf] [[文件:Zhangbo-acl2020-ppt-5-24.pdf]]<br /> <br /> == 2019 ==<br /> * Zhengqiu He, Wenliang Chen, Zhenghua Li, Wei Zhang, Hao Shao, Min Zhang. 2019. Syntax-aware Entity Representations for Neural Relation Extraction. Artificial Intelligence Journal.275(2019):602-617, October 2019.[https://doi.org/10.1016/j.artint.2019.07.004 online version]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Min Zhang. A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling, Proceedings of EMNLP-2019, pp5385-5395, HongKong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1541.pdf PDF]<br /> <br /> * Xiangyu Duan, Hongfei Yu, Mingming Yin, Min Zhang, Weihua Luo, Yue Zhang. Contrastive Attention Mechanism for Abstractive Sentence Summarization, Proceeding of EMNLP-2019, pp3035–3044, Hong Kong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1301 PDF]<br /> <br /> * Hongfei Yu, Xiaoqing Zhou, Xiangyu Duan, Min Zhang. Layer-wise De-training and Re-training for Convolutional Sequence to Sequence Machine Translation, Asian and Low-Resource Language Information Processing, Vol. 19, No. 2, Article 26[J][https://dl.acm.org/citation.cfm?id=3358414 PDF]<br /> <br /> * Xiangyu Duan, Mingming Yin, Min Zhang, Boxing Chen, Weihua Luo. Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention, Proceeding of ACL-2019, pp3162–3172, Florence, Italy, Jul 28 - Aug 2, 2019. [C] [https://www.aclweb.org/anthology/P19-1305 PDF]<br /> <br /> * Zhenghua Li, Xue Peng, Min Zhang, Rui Wang, Luo Si. 2019. Semi-supervised Domain Adaptation for Dependency Parsing. Proceedings of ACL-2019, pp. 2386-2395. Florence, Italy, 28 Jul. - 2 Aug. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua_acl19_dp_2.pdf PDF]<br /> <br /> * Kai SONG, Yue ZHANG, Heng YU, Weihua LUO, Kun WANG and Min ZHANG. Code-Switching for Enhancing NMT with Pre-Specified Translation. Proceedings of the 20th Annual Conference of the North American Chapter of the ACL (NAACL-2019), 136–144, Minneapolis, 2-7 June 2019 [C]<br /> <br /> * Meishan Zhang, Zhenghua Li, Guohong Fu, Min Zhang. 2019. Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations. Proceedings of NAACL-2019, pp. 1151-1161. Minneapolis, Minnesota, America, 2-7 Jun. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhang-naacl-2019.pdf PDF]<br /> <br /> * Ying Li, Zhenghua Li, Min Zhang, Rui Wang, Sheng Li, Luo Si. 2019. Self-attentive Biaffine Dependency Parsing. Proceedings of IJCAI-2019, pp. 5067-5073. Macao, China, 10-16 Aug. 2019 [https://www.ijcai.org/proceedings/2019/0704.pdf PDF]<br /> <br /> * Qingrong Xia, Zhenghua Li, Min Zhang, Meishan Zhang, Guohong Fu, Rui Wang, Luo Si. 2019. Syntax-aware Neural Semantic Role Labeling. Proceedings of AAAI-2019, pp. x-x. Honolulu, Hawaii, America, 27 Jan. - 1 Feb. 2019. [http://hlt.suda.edu.cn/kiro/papers/aaai19.pdf PDF]<br /> <br /> * 周俊佐, 朱宗奎, 何正球, 陈文亮, 张民. 面向人机对话意图分类的混合神经网络模型. 软件学报. 2019,30(11):3313-3325[http://www.jos.org.cn/jos/ch/reader/view_abstract.aspx?file_no=5862&amp;flag=1 PDF]<br /> <br /> == 2018 ==<br /> <br /> * Xinzhou Jiang, Bo Zhang, Zhenghua Li, Min Zhang, Sheng Li, Luo Si. Supervised Treebank Conversion: Data and Approaches. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL-2018), pp. 2706-2716. Melbourne, Australia. 15-20 Jul. 2018[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl18.pdf PDF]<br /> <br /> * Yachao Li, Junhui Li, Min Zhang. Adapted Weights for Neural Machine Translation. In Proceedings of COLING-2018, pp. 3038–3048, Santa Fe, New Mexico, USA, August 20-26, 2018[C]<br /> <br /> * Yaosheng Yang, Wenliang Chen, Zhenghua Li, Zhengqiu He and Min Zhang. Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning, Proceedings of COLING2018, pp.2159–2169, Santa Fe, New Mexico, USA, August 20-26, 2018[C] [https://github.com/rainarch/DSNER Code] [http://aclweb.org/anthology/C18-1183 PDF]<br /> <br /> * Kai Song, Yue Zhang, Min Zhang, Weihua Luo. Improved English to Russian Translation by Neural Suffix Prediction, Proceedings of AAAI-2018, pp410-417, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03615 PDF]<br /> <br /> * YaoSheng Yang, Meishan Zhang, Wenliang Chen*, Haofen Wang, Wei Zhang, Min Zhang. Adversarial Learning for Chinese NER from Crowd Annotations, Proceedings of AAAI-2018, pp1627-1634, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Zhengqiu He, Wenliang Chen*, Zhenghua Li, Meishan Zhang, Wei Zhang, Min Zhang. SEE: Syntax-aware Entity Embedding for Neural Relation Extraction, Proceedings of AAAI-2018, pp5795-5802, New Orleans, USA,Feb 2018[C] [http://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Qi Lu, YaoSheng Yang, Zhenghua Li, Wenliang Chen and Min Zhang. M-CNER: A Corpus for Chinese Named Entity Recognition in Multi-Domains, Proceedings of LREC-2018, pp4458-4461, Japan, May 2018 [http://hlt.suda.edu.cn/~zhli/papers/lrec-2018-ner.pdf PDF]<br /> <br /> == 2017 ==<br /> * Wenliang Chen, Muhua Zhu, Min Zhang, Yue Zhang, Jingbo Zhu. Improving Shift-Reduce Phrase-Structure Parsing with Constituent Boundary Information. Computational Intelligence Journal, 33(3):428-447, August 2017[J]<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen, Meishan Zhang, Guohong Fu. 2016. Coupled POS Tagging on Heterogeneous Annotations. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2017. 25(3), pp. 557-571.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua-ieee17-coupled-pos.pdf PDF]<br /> <br /> * Yue Zhang, Zhenghua Li, Jun Lang, Qingrong Xia, Min Zhang. 2017. Dependency Parsing with Partial Annotations: An Empirical Comparison. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-2017), pp. 49-58. Taiwan, Nov. 27 - Dec. 1, 2017[C] [http://aclweb.org/anthology/I/I17/I17-1006.pdf PDF]<br /> <br /> * Chen Gong, Zhenghua Li, Min Zhang, Xinzhou Jiang. 2017. Multi-Grained Chinese Word Segmentation. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP-2017), pp. 703-714. Copenhagen, Denmark, 7-11 Sept. 2017[C] [http://hlt.suda.edu.cn/~zhli/papers/chen-d17-mws.pdf PDF]<br /> <br /> == 2016 ==<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Jiwen Yang. Fast Coupled Sequence Labeling on Heterogeneous Annotations via Context-aware Pruning. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-2016), pp. 753-762. Austin, Texas, USA, 1-5 Nov. 2016[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-emnlp-2016-submission.pdf PDF]<br /> <br /> * Zhenghua Li, Min Zhang, Yue Zhang, Zhanyi Liu, Wenliang Chen, Hua Wu, Haifeng Wang. Active Learning for Dependency Parsing with Partial Annotation. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-2016), pp. 344-354. Berlin, 7-12 Aug. 2016[C] [http://hlt.suda.edu.cn/~zhli/acl-2016-resources/zhenghua-acl2016-camera-ready.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang, Xiangyu Duan. Exploiting Meta Features for Dependency Parsing and Part-of-speech Tagging. Artificial Intelligence Journal, 230(2016):173-191, January 2016[J]<br /> <br /> * Wenliang Chen, Zhenjie Zhang, Zhenghua Li, Min Zhang. Distributed Representations for Building Profiles of Users and Items from Text Reviews. In Proc. of the 26th International Conference on Computational Linguistics (COLING-2016), pp2143-2153, Osaka, 11-17 Dec. 2016[C][https://www.aclweb.org/anthology/C16-1202.pdf PDF]<br /> <br /> == 2015 ==<br /> *Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen. 2015. Coupled Sequence Labeling on Heterogeneous Annotations: POS Tagging as a Case Study. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-2015), pp. 1783-1792. Beijing, 26-31 July 2015[C] [http://aclweb.org/anthology/P/P15/P15-1172.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> == 2014 ==<br /> *Zhenghua Li, Min Zhang, Wanxiang Che, Ting Liu, Wenliang Chen. 2014. Joint Optimization for Chinese POS Tagging and Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2014. 22(1), pp. 274-286.[J] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-taslp14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Soft Cross-lingual Syntax Projection for Dependency Parsing. Proceedings of the 25th International Conference on Computational Linguistics (COLING-2014), pp. 783-793. Dublin, 23-29 Aug. 2014[C][http://hlt.suda.edu.cn/~zhli/papers/zhenghua-coling14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Ambiguity-aware Ensemble Training for Semi-supervised Dependency Parsing. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL-2014), pp. 457-467. Baltimore, 22-27 June 2014[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl14.pdf PDF] <br /> <br /> * Min ZHANG, Xiangyu Duan, Wenliang CHEN. Bayesian Constituent Context Model for Grammar Induction. IEEE/ACM Transactions on Audio, Speech and Language Processing, 22(2):531-541, 2014[J]<br /> <br /> * Xiangyu Duan, Min Zhang, Qiaoming Zhu. Synchronous Constituent Context Model for Inducing Bilingual Synchronous Structures. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp783-793, Dublin, Ireland, August 2014<br /> <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp816-826, Dublin, Ireland, August 2014<br /> <br /> == 2013 ==<br /> * Min Zhang, Wenliang Chen*, Xiangyu Duan, and Rong Zhang. Improving Graph-based Dependency Parsing Models with Dependency Language Models. IEEE Transactions on Audio, Speech and Language Processing (IEEE-TASL), Vol.21, No.11, pp2313-2323 November 2013. <br /> <br /> * Muhua Zhu, Yue Zhang, Wenliang Chen, Min Zhang, and Jingbo Zhu. Fast and Accurate Constituent Parsing. In Proc. of ACL2013, pp 434-443, Sofia, Bulgaria, August 2013.<br /> <br /> * Xiangyu Duan, Min Zhang, Wenliang Chen. Smoothing for Bracketing Induction. In Proc. of IJCAI2013, pp 2085-2091, Beijing, China, August 2013.<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang. Semi-Supervised Feature Transformation for Dependency Parsing. In Proc. of EMNLP2013, pp1303-1313, Seattle, Washington, USA, 18-21 October 2013.<br /> <br /> == 更古老 ==<br /> <br /> * 请查看各位成员的主页<br /> <br /> <br /> == 参考格式 ==<br /> 期刊格式：[作者列表]. [题目]. [期刊名], [卷号(期):起止页码], [年份][J]<br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> 会议格式：[作者列表]. [题目]. [In Proc. of 会议名], [起止页码], [地点], [会议时间][C] <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING-2014), pp816-826, Dublin, Ireland, August 2014[C]<br /> <br /> 录用格式：[作者列表]. [题目]. [期刊名/会议名], 已录用<br /> * Wenliang Chen. Feature Embedding for Dependency Parsing. CCL-2017, 已录用</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Papers&diff=5417 2024-03-11T04:20:09Z

<p>Xjshi：/* 2023 */</p> <hr /> <div>文章(格式见页尾)包括：<br /> * xACL(ACL/NAACL/EACL/AACL) EMNLP IJCAI AAAI COLING IJCNLP NLPCC<br /> * CCF-A/B Journal/Conference<br /> * SCI Journal<br /> * 软件学报/计算机学报/中国科学<br /> <br /> == [http://hlt.suda.edu.cn/index.php/Papers-details 论文摘要等信息] ==<br /> <br /> == 最新录用 ==<br /> <br /> * Jianxiang Xiang, Zhenhua Liu, Haodong Liu, Yin Bai, Jia Cheng and Wenliang Chen. DiffusionDialog: Diverse Dialog Generation Model with Diffusion in Latent Space. LREC-COLING-2024.<br /> * Tianwen Tang, Tong Zhu, Haodong Liu, Yin Bai, Jia Cheng and Wenliang Chen. MPPE-DST: Mixture of Prefix Prompt Experts for LLM in Zero-Shot Dialogue State Tracking. LREC-COLING-2024.<br /> * Junjie Yu, Xing Wang, and Wenliang Chen. Reliable Data Generation and Selection for Low-Resource Relation Extraction. AAAI-2024.<br /> <br /> * Chuanqi Dong, Wenjie Zhou, Xiangyu Duan, Yuqi Zhang and Min Zhang: Multimodal Cross-lingual Phrase Retrieval, COLING 2024.<br /> * Baijun Ji, Xiangyu Duan, Zhenyu Qiu, Tong Zhang, Junhui Li, Hao Yang and Min Zhang: Submodular-based In-context Example Selection for LLMs-based Machine Translation, COLING 2024.<br /> * Wenjie Zhou, Qiang Wang, Mingzhou Xu, MING CHEN and Xiangyu Duan: Revisiting the Self-Consistency Challenges in Multi-Choice Question Formats for Large Language Model Evaluation, Short Paper, COLING 2024.<br /> <br /> == 2023 ==<br /> <br /> * Tong Zhu, Junfei Ren, Zijian Yu, Mengsong Wu, Guoliang Zhang, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Min Zhang. Mirror: A Universal Framework for Various Information Extraction Tasks. The 2023 Conference on Empirical Methods in Natural Language Processing. 2023.<br /> * Tong Zhu, Guoliang Zhang, Zechang Li, Zijian Yu, Junfei Ren, Mengsong Wu, Zhefeng Wang, Baoxing Huai, Pingfu Chao, Wenliang Chen. CED: Catalog Extraction from Documents. The 17th International Conference on Document Analysis and Recognition. 2023.<br /> * Mian Zhang, Xiabing Zhou, Wenliang Chen, Min Zhang. Emotion Recognition in Coversation from Variable-lenght Context. ICASSP 2023.<br /> * Houquan Zhou, Yumeng Liu, Zhenghua Li*, Min Zhang, Bo Zhang, Chen Li, Ji Zhang, Fei Huang. 2023. Improving Seq2Seq Grammatical Error Correction via Decoding Interventions. Findings of '''EMNLP''', pages 7393–7405. [https://arxiv.org/abs/2310.14534 arxiv][https://github.com/Jacob-Zhou/gecdi code][https://www.semanticscholar.org/paper/Improving-Seq2Seq-Grammatical-Error-Correction-via-Zhou-Liu/4711f26c0295fed15161b6145800b3df1ab9c0f6 citation]<br /> * Yue Zhang, Leyang Cui, Enbo Zhao, Wei Bi, Shuming Shi. 2023. RobustGEC: Robust Grammatical Error Correction Against Subtle Context Perturbation. EMNLP 2023.[https://arxiv.org/pdf/2310.07299.pdf arxiv] [https://github.com/hillzhang1999/RobustGEC code]<br /> * Saihao Huang, Lijie Wang, Zhenghua Li*, Zeyang Liu, Chenhui Dou, Fukang Yan, Xinyan Xiao, Hua Wu, and Min Zhang. 2023. SeSQL: A High-Quality Large-Scale Session-Level Chinese Text-to-SQL Dataset. NLPCC 2023, pages 537-550.[[文件:SeSQL_A_High-Quality_Large-Scale_Session-Level_Chinese_Text-to-SQL_Dataset.pdf]] [https://arxiv.org/abs/2208.12711 arxiv]<br /> * Yue Zhang, Bo Zhang, Haochen Jiang, Zhenghua Li*, Chen Li, Fei Huang, Min Zhang. 2023. NaSGEC: Multi-Domain Chinese Grammatical Error Correction for Native Speaker Texts. Findings of ACL 2023. pp 9935-9951. [https://aclanthology.org/2023.findings-acl.630.pdf official] [https://arxiv.org/pdf/2305.16023.pdf arxiv] [https://github.com/HillZhang1999/NaSGEC code]<br /> * Jinpeng Zhang, Nini Xiao, Ke Wang, Chuanqi Dong, Xiangyu Duan*, Yuqi Zhang, Min Zhang: Disambiguated Lexically Constrained Neural Machine Translation, ACL 2023 Findings.<br /> <br /> == 2022 ==<br /> <br /> <br /> * Yahui Liu, Haoping Yang, Chen Gong*, Qingrong Xia, Zhenghua Li, Min Zhang. 2022. MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset. In '''NAACL'''. [http://arxiv.org/abs/2205.06703 arxiv]<br /> * Yue Zhang, Zhenghua Li*, Zuyi Bao, Jiacheng Li, Bo Zhang, Chen Li, Fei Huang, Min Zhang. 2022. MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction. In '''NAACL'''. [https://arxiv.org/abs/2204.10994 arxiv]<br /> * Ying Li, Shuaike Li, Min Zhang. 2022. Semi-supervised Domain Adaptation for Dependency Parsing with Dynamic Matching Network. In '''ACL 2022'', pages 1035--1045. [https://aclanthology.org/2022.acl-long.74.pdf official-pdf] [http://hlt.suda.edu.cn/index.php/%E6%96%87%E4%BB%B6:Liying_ACL2022_camera_ready.pdf camera ready pdf] [https://underline.io/lecture/52551-long-semi-supervised-domain-adaptation-for-dependency-parsing-with-dynamic-matching-network video].<br /> * Houquan Zhou, Yang Li, Zhenghua Li, and Min Zhang. 2022. Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging. In Findings of the Association for Computational Linguistics: ACL 2022, pages 3276–3290, Dublin, Ireland. Association for Computational Linguistics. [http://hlt.suda.edu.cn/LA/papers/acl-findings-hqzhou-bridging.pdf pdf] [https://arxiv.org/pdf/2203.10315 camera ready pdf] [https://aclanthology.org/2022.findings-acl.259.pdf offcial pdf] [https://underline.io/lecture/49965-findings-bridging-pre-trained-language-models-and-hand-crafted-features-for-unsupervised-pos-tagging video]<br /> * Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Yuan, Min Zhang. Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph. IJCAI. 2022<br /> * Chang Jin, Shigui Qiu, Nini Xiao, Hao Jia. AdMix: A Mixed Sample Data Augmentation Method for Neural Machine Translation. IJCAI. 2022<br /> * Xiabing Zhou, Renjie Feng, Xiaotong Jiang, and ZhongqingWang. Exploring Logographic Image for Chinese Aspect-based Sentiment. EMNLP(findings),2022<br /> <br /> == 2021 ==<br /> <br /> * Yang Hou, Houquan Zhou, Zhenghua Li*, Yu Zhang, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. A Coarse-to-Fine Labeling Framework for Joint Word Segmentation, POS Tagging, and Constituent Parsing. Proceedings of CoNLL-2021, pp. 290–299. Punta Cana, Dominican Republic (Online), 10-11 Nov. 2021. [[文件:CoNLL_2021_yhou_official_version.pdf]]<br /> <br /> * Kun Wu, Lijie Wang, Zhenghua Li, Ao Zhang, Xinyan Xiao, Hua Wu, Min Zhang, Haifeng Wang. Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-Domain Text-to-SQL Parsing. Proceedings of EMNLP-2021, pp. 8974--8983. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP2021_camera_ready_Data_Augmentation_with_Hierarchical_SQL_to_Question_Generation_forCross_domain_Text_to_SQL_Parsing-09101500.pdf ‎]]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Rui Wang, Min Zhang. Stacked AMR Parsing with Silver Data. Proceedings of EMNLP-2021 Findings, pp. 4729--4738. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_Stacked_AMR_Parsing_with_Silver_Data.pdf]]<br /> <br /> * Ying Li, Meishan Zhang, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. APGN: Adversarial and Parameter Generation Networks for Multi-Source Cross-Domain Dependency Parsing. Proceedings of EMNLP-2021 Findings, pp. 1727–1733. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_yli_camera_ready.pdf]]<br /> <br /> * Chen Gong, Saihao Huang, Houquan Zhou, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. An In-depth Study on Internal Structure of Chinese Words. Proceedings of ACL-2021, pp. 5823–5833. Online, Virtual Event, 1-6 Aug. 2021. [[文件:2021.acl-long.452.pdf]]<br /> <br /> * Qingrong Xia, Bo Zhang, Rui Wang, Zhenghua Li*, Yue Zhang, Fei Huang, Luo Si, Min Zhang. 2021. A Unified Span-Based Approach for Opinion Mining with Syntactic Constituents. Proceedings of NAACL-2021, pp. 1795-1804. Mexico City, Mexico (Online), 6-11 June. 2021. [[文件:2021.naacl-main.144.pdf]]<br /> <br /> * Jinpeng Zhang, Baijun Ji, Nini Xiao, Xiangyu Duan*, Min Zhang, Yangbin Shi, Weihua Luo: Combining Static Word Embeddings and Contextual Representations for Bilingual Lexicon Induction, ACL 2021 Findings. [https://aclanthology.org/2021.findings-acl.260.pdf anthology]<br /> <br /> == 2020 == <br /> <br /> * Zhengqiu HE, Wenliang CHEN, Yuyi WANG, Wei ZHANG, Gaochun WANG, Min ZHANG. Improving Neural Relation Extraction with Positive and Unlabeled Learning. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), pp. 7927-7934. New York, 7-12 Feb. 2020，<br /> <br /> * 杨一帆, 马进, 王海涛, 何正球，陈文亮，张民. 基于简介文本的中文人物关系图谱属性补全与纠错. 中国科学-信息科学. V50(7) : 1003-1018(2020)<br /> <br /> * Junjie Yu, Tong Zhu, Wenliang Chen, Wei Zhang and Min Zhang. Improving Relation Extraction with Relational Paraphrase Sentences. COLING2020, pp. 1687-1698. Online, Dec. 2020[http://hlt.suda.edu.cn/images/9/96/Coling2020-junjie2073_Paper.pdf pdf]<br /> <br /> * Tong Zhu, Haitao Wang, Junjie Yu, Xiabing Zhou, Wenliang Chen, Wei Zhang and Min Zhang. Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction. COLING2020. pp. 6436-6447, Online, Dec. 2020 [https://arxiv.org/pdf/2010.16275.pdf pdf], [https://github.com/Spico197/NYT-H 数据下载@github]<br /> <br /> * Baijun JI, Zhirui ZHANG, Xiangyu DUAN, Min ZHANG, Boxing CHEN and Weihua LUO. Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Xiangyu Duan, Baijun Ji, Hao Jia, Min Tan, Min Zhang, Boxing Chen, Weihua Luo, Yue Zhang: Bilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences. The 58th Annual Meeting of the Association for Computational Linguistics (ACL-2020).<br /> <br /> * Kai SONG, Kun WANG, Heng YU, Yue ZHANG, Zhongqiang HUANG, Weihua LUO, Xiangyu DUAN and Min ZHANG. Alignment-Enhanced Transformer for Constraining NMT with Pre-Specified Translations. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Kai Song, Xiaoqing Zhou, Heng Yu, Zhongqiang Huang, Yue Zhang, Weihua Luo, Xiangyu Duan, Min Zhang: Towards Better Word Alignment in Transformer. IEEE ACM Transaction Audio Speech Language Processing (TASLP), 2020.<br /> <br /> * Huaao Zhang,Shigui Qiu, Xiangyu Duan*,Min Zhang: Token Drop mechanism for Neural Machine Translation. The International Conference on Computational Linguistics (Coling-2020) (short paper).<br /> <br /> * Chen Gong, Zhenghua Li, Qingrong Xia, Wenliang Chen and Min Zhang. Hierarchical LSTM with char-subword-word tree-structure representation for Chinese named entity recognition. Science China Information Science, 2020, 63(10):1-15. [[文件:Hierarchical_LSTM_with_char-subword-word_tree-structure_representation_for_Chinese_named_entity_recognition.pdf]]<br /> <br /> * Ying Li, Zhenghua Li* and Min Zhang. Semi-supervised Domain Adaptation for Dependency Parsing via Improved Contextualized Word Representations. Proceedings of COLING-2020. pp. 3806–3817. Barcelona, Spain (Online), 8-13 Dec. 2020.[https://www.aclweb.org/anthology/2020.coling-main.338.pdf pdf] [[文件:Liying-2020.coling-main.338.pdf]]<br /> <br /> * Qingrong Xia, Rui Wang, Zhenghua Li, Yue Zhang and Min Zhang*. Semantic Role Labeling with Heterogeneous Syntactic Knowledge. Proceedings of COLING-2020. pp. 2979-2990. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/2020.coling-main.266.pdf pdf][[文件:Xiaqingrong-2020.coling-main.266.pdf]]<br /> <br /> * Chen Gong, Zhenghua Li*, Bowei Zou and Min Zhang. Multi-grained Chinese Word Segmentation with Weakly Labeled Data. Proceedings of COLING-2020. pp. 2026–2036. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/D17-1072.pdf pdf][[文件:Gongchen-2020.coling-main.183.pdf]]<br /> <br /> * Lijie Wang, Ao Zhang, Kun Wu, Ke Sun, Zhenghua Li, Hua Wu*, Min Zhang and Haifeng Wang. DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset. Proceedings of EMNLP-2020. pp. 6923-6935. Online, 16-20 Nov. 2020. [https://www.aclweb.org/anthology/2020.emnlp-main.562.pdf pdf][[文件:2020.emnlp-main.562.pdf]]<br /> <br /> * Houquan Zhou, Yu Zhang, Zhenghua Li, and Min Zhang. Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing? Proceedings of NLPCC-2020, pp. 179--191. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo.pdf pdf]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official-w-content.pdf pdf-official-w-content]) &lt;font color=&quot;#FF0000&quot;&gt;&lt;b&gt;(best paper!)&lt;/b&gt;&lt;/font&gt; <br /> <br /> * Yu Zhao, Mingyue Zhou, Zhenghua Li, and Min Zhang. Dependency Parsing with Noisy Multi-Annotation Data. Proceedings of NLPCC-2020, pp. 120-131. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/images/e/e5/212_Final_Manuscript_%281%29.pdf pdf]）([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official-w-content.pdf pdf-official-w-content])<br /> <br /> * Yu Zhang, Houquan Zhou, Zhenghua Li. 2020. Fast and Accurate Neural CRF Constituency Parsing. Proceedings of IJCAI-2020, pp. 4046-4053. Yokohama, Japan, 11-17 Jul. 2020. [https://www.ijcai.org/Proceedings/2020/0560.pdf pdf-official] [http://hlt.suda.edu.cn/LA/papers/0560.pdf pdf] [[http://hlt.suda.edu.cn/LA/videos/V5.mp4 video(5 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V10.mp4 video(10 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V15.mp4 video(15 min version)]]<br /> <br /> * Yu Zhang, Zhenghua Li, Min Zhang. 2020. Efficient Second-Order TreeCRF for Neural Dependency Parsing. Proceedings of ACL-2020, pp. 3295-3305. Seattle, America, 5-10 Jul. 2020. ][https://www.aclweb.org/anthology/2020.acl-main.302.pdf pdf-official]] [[http://hlt.suda.edu.cn/LA/papers/2020.acl-main.302.pdf pdf]] [[http://hlt.suda.edu.cn/LA/videos/2020-12-28%2022-21-45.mp4 video]]<br /> <br /> * Bo Zhang, Yue Zhang, Rui Wang, Zhenghua Li, Min Zhang. Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks. Proceedings of ACL-2020, pp. 3249-3258. Seattle, America, 5-10 Jul. 2020. [https://www.aclweb.org/anthology/2020.acl-main.297.pdf pdf] [[文件:Zhangbo-acl2020-ppt-5-24.pdf]]<br /> <br /> == 2019 ==<br /> * Zhengqiu He, Wenliang Chen, Zhenghua Li, Wei Zhang, Hao Shao, Min Zhang. 2019. Syntax-aware Entity Representations for Neural Relation Extraction. Artificial Intelligence Journal.275(2019):602-617, October 2019.[https://doi.org/10.1016/j.artint.2019.07.004 online version]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Min Zhang. A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling, Proceedings of EMNLP-2019, pp5385-5395, HongKong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1541.pdf PDF]<br /> <br /> * Xiangyu Duan, Hongfei Yu, Mingming Yin, Min Zhang, Weihua Luo, Yue Zhang. Contrastive Attention Mechanism for Abstractive Sentence Summarization, Proceeding of EMNLP-2019, pp3035–3044, Hong Kong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1301 PDF]<br /> <br /> * Hongfei Yu, Xiaoqing Zhou, Xiangyu Duan, Min Zhang. Layer-wise De-training and Re-training for Convolutional Sequence to Sequence Machine Translation, Asian and Low-Resource Language Information Processing, Vol. 19, No. 2, Article 26[J][https://dl.acm.org/citation.cfm?id=3358414 PDF]<br /> <br /> * Xiangyu Duan, Mingming Yin, Min Zhang, Boxing Chen, Weihua Luo. Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention, Proceeding of ACL-2019, pp3162–3172, Florence, Italy, Jul 28 - Aug 2, 2019. [C] [https://www.aclweb.org/anthology/P19-1305 PDF]<br /> <br /> * Zhenghua Li, Xue Peng, Min Zhang, Rui Wang, Luo Si. 2019. Semi-supervised Domain Adaptation for Dependency Parsing. Proceedings of ACL-2019, pp. 2386-2395. Florence, Italy, 28 Jul. - 2 Aug. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua_acl19_dp_2.pdf PDF]<br /> <br /> * Kai SONG, Yue ZHANG, Heng YU, Weihua LUO, Kun WANG and Min ZHANG. Code-Switching for Enhancing NMT with Pre-Specified Translation. Proceedings of the 20th Annual Conference of the North American Chapter of the ACL (NAACL-2019), 136–144, Minneapolis, 2-7 June 2019 [C]<br /> <br /> * Meishan Zhang, Zhenghua Li, Guohong Fu, Min Zhang. 2019. Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations. Proceedings of NAACL-2019, pp. 1151-1161. Minneapolis, Minnesota, America, 2-7 Jun. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhang-naacl-2019.pdf PDF]<br /> <br /> * Ying Li, Zhenghua Li, Min Zhang, Rui Wang, Sheng Li, Luo Si. 2019. Self-attentive Biaffine Dependency Parsing. Proceedings of IJCAI-2019, pp. 5067-5073. Macao, China, 10-16 Aug. 2019 [https://www.ijcai.org/proceedings/2019/0704.pdf PDF]<br /> <br /> * Qingrong Xia, Zhenghua Li, Min Zhang, Meishan Zhang, Guohong Fu, Rui Wang, Luo Si. 2019. Syntax-aware Neural Semantic Role Labeling. Proceedings of AAAI-2019, pp. x-x. Honolulu, Hawaii, America, 27 Jan. - 1 Feb. 2019. [http://hlt.suda.edu.cn/kiro/papers/aaai19.pdf PDF]<br /> <br /> * 周俊佐, 朱宗奎, 何正球, 陈文亮, 张民. 面向人机对话意图分类的混合神经网络模型. 软件学报. 2019,30(11):3313-3325[http://www.jos.org.cn/jos/ch/reader/view_abstract.aspx?file_no=5862&amp;flag=1 PDF]<br /> <br /> == 2018 ==<br /> <br /> * Xinzhou Jiang, Bo Zhang, Zhenghua Li, Min Zhang, Sheng Li, Luo Si. Supervised Treebank Conversion: Data and Approaches. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL-2018), pp. 2706-2716. Melbourne, Australia. 15-20 Jul. 2018[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl18.pdf PDF]<br /> <br /> * Yachao Li, Junhui Li, Min Zhang. Adapted Weights for Neural Machine Translation. In Proceedings of COLING-2018, pp. 3038–3048, Santa Fe, New Mexico, USA, August 20-26, 2018[C]<br /> <br /> * Yaosheng Yang, Wenliang Chen, Zhenghua Li, Zhengqiu He and Min Zhang. Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning, Proceedings of COLING2018, pp.2159–2169, Santa Fe, New Mexico, USA, August 20-26, 2018[C] [https://github.com/rainarch/DSNER Code] [http://aclweb.org/anthology/C18-1183 PDF]<br /> <br /> * Kai Song, Yue Zhang, Min Zhang, Weihua Luo. Improved English to Russian Translation by Neural Suffix Prediction, Proceedings of AAAI-2018, pp410-417, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03615 PDF]<br /> <br /> * YaoSheng Yang, Meishan Zhang, Wenliang Chen*, Haofen Wang, Wei Zhang, Min Zhang. Adversarial Learning for Chinese NER from Crowd Annotations, Proceedings of AAAI-2018, pp1627-1634, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Zhengqiu He, Wenliang Chen*, Zhenghua Li, Meishan Zhang, Wei Zhang, Min Zhang. SEE: Syntax-aware Entity Embedding for Neural Relation Extraction, Proceedings of AAAI-2018, pp5795-5802, New Orleans, USA,Feb 2018[C] [http://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Qi Lu, YaoSheng Yang, Zhenghua Li, Wenliang Chen and Min Zhang. M-CNER: A Corpus for Chinese Named Entity Recognition in Multi-Domains, Proceedings of LREC-2018, pp4458-4461, Japan, May 2018 [http://hlt.suda.edu.cn/~zhli/papers/lrec-2018-ner.pdf PDF]<br /> <br /> == 2017 ==<br /> * Wenliang Chen, Muhua Zhu, Min Zhang, Yue Zhang, Jingbo Zhu. Improving Shift-Reduce Phrase-Structure Parsing with Constituent Boundary Information. Computational Intelligence Journal, 33(3):428-447, August 2017[J]<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen, Meishan Zhang, Guohong Fu. 2016. Coupled POS Tagging on Heterogeneous Annotations. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2017. 25(3), pp. 557-571.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua-ieee17-coupled-pos.pdf PDF]<br /> <br /> * Yue Zhang, Zhenghua Li, Jun Lang, Qingrong Xia, Min Zhang. 2017. Dependency Parsing with Partial Annotations: An Empirical Comparison. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-2017), pp. 49-58. Taiwan, Nov. 27 - Dec. 1, 2017[C] [http://aclweb.org/anthology/I/I17/I17-1006.pdf PDF]<br /> <br /> * Chen Gong, Zhenghua Li, Min Zhang, Xinzhou Jiang. 2017. Multi-Grained Chinese Word Segmentation. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP-2017), pp. 703-714. Copenhagen, Denmark, 7-11 Sept. 2017[C] [http://hlt.suda.edu.cn/~zhli/papers/chen-d17-mws.pdf PDF]<br /> <br /> == 2016 ==<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Jiwen Yang. Fast Coupled Sequence Labeling on Heterogeneous Annotations via Context-aware Pruning. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-2016), pp. 753-762. Austin, Texas, USA, 1-5 Nov. 2016[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-emnlp-2016-submission.pdf PDF]<br /> <br /> * Zhenghua Li, Min Zhang, Yue Zhang, Zhanyi Liu, Wenliang Chen, Hua Wu, Haifeng Wang. Active Learning for Dependency Parsing with Partial Annotation. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-2016), pp. 344-354. Berlin, 7-12 Aug. 2016[C] [http://hlt.suda.edu.cn/~zhli/acl-2016-resources/zhenghua-acl2016-camera-ready.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang, Xiangyu Duan. Exploiting Meta Features for Dependency Parsing and Part-of-speech Tagging. Artificial Intelligence Journal, 230(2016):173-191, January 2016[J]<br /> <br /> * Wenliang Chen, Zhenjie Zhang, Zhenghua Li, Min Zhang. Distributed Representations for Building Profiles of Users and Items from Text Reviews. In Proc. of the 26th International Conference on Computational Linguistics (COLING-2016), pp2143-2153, Osaka, 11-17 Dec. 2016[C][https://www.aclweb.org/anthology/C16-1202.pdf PDF]<br /> <br /> == 2015 ==<br /> *Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen. 2015. Coupled Sequence Labeling on Heterogeneous Annotations: POS Tagging as a Case Study. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-2015), pp. 1783-1792. Beijing, 26-31 July 2015[C] [http://aclweb.org/anthology/P/P15/P15-1172.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> == 2014 ==<br /> *Zhenghua Li, Min Zhang, Wanxiang Che, Ting Liu, Wenliang Chen. 2014. Joint Optimization for Chinese POS Tagging and Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2014. 22(1), pp. 274-286.[J] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-taslp14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Soft Cross-lingual Syntax Projection for Dependency Parsing. Proceedings of the 25th International Conference on Computational Linguistics (COLING-2014), pp. 783-793. Dublin, 23-29 Aug. 2014[C][http://hlt.suda.edu.cn/~zhli/papers/zhenghua-coling14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Ambiguity-aware Ensemble Training for Semi-supervised Dependency Parsing. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL-2014), pp. 457-467. Baltimore, 22-27 June 2014[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl14.pdf PDF] <br /> <br /> * Min ZHANG, Xiangyu Duan, Wenliang CHEN. Bayesian Constituent Context Model for Grammar Induction. IEEE/ACM Transactions on Audio, Speech and Language Processing, 22(2):531-541, 2014[J]<br /> <br /> * Xiangyu Duan, Min Zhang, Qiaoming Zhu. Synchronous Constituent Context Model for Inducing Bilingual Synchronous Structures. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp783-793, Dublin, Ireland, August 2014<br /> <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp816-826, Dublin, Ireland, August 2014<br /> <br /> == 2013 ==<br /> * Min Zhang, Wenliang Chen*, Xiangyu Duan, and Rong Zhang. Improving Graph-based Dependency Parsing Models with Dependency Language Models. IEEE Transactions on Audio, Speech and Language Processing (IEEE-TASL), Vol.21, No.11, pp2313-2323 November 2013. <br /> <br /> * Muhua Zhu, Yue Zhang, Wenliang Chen, Min Zhang, and Jingbo Zhu. Fast and Accurate Constituent Parsing. In Proc. of ACL2013, pp 434-443, Sofia, Bulgaria, August 2013.<br /> <br /> * Xiangyu Duan, Min Zhang, Wenliang Chen. Smoothing for Bracketing Induction. In Proc. of IJCAI2013, pp 2085-2091, Beijing, China, August 2013.<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang. Semi-Supervised Feature Transformation for Dependency Parsing. In Proc. of EMNLP2013, pp1303-1313, Seattle, Washington, USA, 18-21 October 2013.<br /> <br /> == 更古老 ==<br /> <br /> * 请查看各位成员的主页<br /> <br /> <br /> == 参考格式 ==<br /> 期刊格式：[作者列表]. [题目]. [期刊名], [卷号(期):起止页码], [年份][J]<br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> 会议格式：[作者列表]. [题目]. [In Proc. of 会议名], [起止页码], [地点], [会议时间][C] <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING-2014), pp816-826, Dublin, Ireland, August 2014[C]<br /> <br /> 录用格式：[作者列表]. [题目]. [期刊名/会议名], 已录用<br /> * Wenliang Chen. Feature Embedding for Dependency Parsing. CCL-2017, 已录用</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Papers&diff=5416 2024-03-11T04:18:28Z

<p>Xjshi：/* 最新录用 */</p> <hr /> <div>文章(格式见页尾)包括：<br /> * xACL(ACL/NAACL/EACL/AACL) EMNLP IJCAI AAAI COLING IJCNLP NLPCC<br /> * CCF-A/B Journal/Conference<br /> * SCI Journal<br /> * 软件学报/计算机学报/中国科学<br /> <br /> == [http://hlt.suda.edu.cn/index.php/Papers-details 论文摘要等信息] ==<br /> <br /> == 最新录用 ==<br /> <br /> * Jianxiang Xiang, Zhenhua Liu, Haodong Liu, Yin Bai, Jia Cheng and Wenliang Chen. DiffusionDialog: Diverse Dialog Generation Model with Diffusion in Latent Space. LREC-COLING-2024.<br /> * Tianwen Tang, Tong Zhu, Haodong Liu, Yin Bai, Jia Cheng and Wenliang Chen. MPPE-DST: Mixture of Prefix Prompt Experts for LLM in Zero-Shot Dialogue State Tracking. LREC-COLING-2024.<br /> * Junjie Yu, Xing Wang, and Wenliang Chen. Reliable Data Generation and Selection for Low-Resource Relation Extraction. AAAI-2024.<br /> <br /> * Chuanqi Dong, Wenjie Zhou, Xiangyu Duan, Yuqi Zhang and Min Zhang: Multimodal Cross-lingual Phrase Retrieval, COLING 2024.<br /> * Baijun Ji, Xiangyu Duan, Zhenyu Qiu, Tong Zhang, Junhui Li, Hao Yang and Min Zhang: Submodular-based In-context Example Selection for LLMs-based Machine Translation, COLING 2024.<br /> * Wenjie Zhou, Qiang Wang, Mingzhou Xu, MING CHEN and Xiangyu Duan: Revisiting the Self-Consistency Challenges in Multi-Choice Question Formats for Large Language Model Evaluation, Short Paper, COLING 2024.<br /> <br /> == 2023 ==<br /> <br /> * Tong Zhu, Junfei Ren, Zijian Yu, Mengsong Wu, Guoliang Zhang, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Min Zhang. Mirror: A Universal Framework for Various Information Extraction Tasks. The 2023 Conference on Empirical Methods in Natural Language Processing. 2023.<br /> * Tong Zhu, Guoliang Zhang, Zechang Li, Zijian Yu, Junfei Ren, Mengsong Wu, Zhefeng Wang, Baoxing Huai, Pingfu Chao, Wenliang Chen. CED: Catalog Extraction from Documents. The 17th International Conference on Document Analysis and Recognition. 2023.<br /> * Mian Zhang, Xiabing Zhou, Wenliang Chen, Min Zhang. Emotion Recognition in Coversation from Variable-lenght Context. ICASSP 2023.<br /> * Houquan Zhou, Yumeng Liu, Zhenghua Li*, Min Zhang, Bo Zhang, Chen Li, Ji Zhang, Fei Huang. 2023. Improving Seq2Seq Grammatical Error Correction via Decoding Interventions. Findings of '''EMNLP''', pages 7393–7405. [https://arxiv.org/abs/2310.14534 arxiv][https://github.com/Jacob-Zhou/gecdi code][https://www.semanticscholar.org/paper/Improving-Seq2Seq-Grammatical-Error-Correction-via-Zhou-Liu/4711f26c0295fed15161b6145800b3df1ab9c0f6 citation]<br /> * Yue Zhang, Leyang Cui, Enbo Zhao, Wei Bi, Shuming Shi. 2023. RobustGEC: Robust Grammatical Error Correction Against Subtle Context Perturbation. EMNLP 2023.[https://arxiv.org/pdf/2310.07299.pdf arxiv] [https://github.com/hillzhang1999/RobustGEC code]<br /> * Saihao Huang, Lijie Wang, Zhenghua Li*, Zeyang Liu, Chenhui Dou, Fukang Yan, Xinyan Xiao, Hua Wu, and Min Zhang. 2023. SeSQL: A High-Quality Large-Scale Session-Level Chinese Text-to-SQL Dataset. NLPCC 2023, pages 537-550.[[文件:SeSQL_A_High-Quality_Large-Scale_Session-Level_Chinese_Text-to-SQL_Dataset.pdf]] [https://arxiv.org/abs/2208.12711 arxiv]<br /> * Yue Zhang, Bo Zhang, Haochen Jiang, Zhenghua Li*, Chen Li, Fei Huang, Min Zhang. 2023. NaSGEC: Multi-Domain Chinese Grammatical Error Correction for Native Speaker Texts. Findings of ACL 2023. pp 9935-9951. [https://aclanthology.org/2023.findings-acl.630.pdf official] [https://arxiv.org/pdf/2305.16023.pdf arxiv] [https://github.com/HillZhang1999/NaSGEC code]<br /> <br /> == 2022 ==<br /> <br /> <br /> * Yahui Liu, Haoping Yang, Chen Gong*, Qingrong Xia, Zhenghua Li, Min Zhang. 2022. MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset. In '''NAACL'''. [http://arxiv.org/abs/2205.06703 arxiv]<br /> * Yue Zhang, Zhenghua Li*, Zuyi Bao, Jiacheng Li, Bo Zhang, Chen Li, Fei Huang, Min Zhang. 2022. MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction. In '''NAACL'''. [https://arxiv.org/abs/2204.10994 arxiv]<br /> * Ying Li, Shuaike Li, Min Zhang. 2022. Semi-supervised Domain Adaptation for Dependency Parsing with Dynamic Matching Network. In '''ACL 2022'', pages 1035--1045. [https://aclanthology.org/2022.acl-long.74.pdf official-pdf] [http://hlt.suda.edu.cn/index.php/%E6%96%87%E4%BB%B6:Liying_ACL2022_camera_ready.pdf camera ready pdf] [https://underline.io/lecture/52551-long-semi-supervised-domain-adaptation-for-dependency-parsing-with-dynamic-matching-network video].<br /> * Houquan Zhou, Yang Li, Zhenghua Li, and Min Zhang. 2022. Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging. In Findings of the Association for Computational Linguistics: ACL 2022, pages 3276–3290, Dublin, Ireland. Association for Computational Linguistics. [http://hlt.suda.edu.cn/LA/papers/acl-findings-hqzhou-bridging.pdf pdf] [https://arxiv.org/pdf/2203.10315 camera ready pdf] [https://aclanthology.org/2022.findings-acl.259.pdf offcial pdf] [https://underline.io/lecture/49965-findings-bridging-pre-trained-language-models-and-hand-crafted-features-for-unsupervised-pos-tagging video]<br /> * Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Yuan, Min Zhang. Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph. IJCAI. 2022<br /> * Chang Jin, Shigui Qiu, Nini Xiao, Hao Jia. AdMix: A Mixed Sample Data Augmentation Method for Neural Machine Translation. IJCAI. 2022<br /> * Xiabing Zhou, Renjie Feng, Xiaotong Jiang, and ZhongqingWang. Exploring Logographic Image for Chinese Aspect-based Sentiment. EMNLP(findings),2022<br /> <br /> == 2021 ==<br /> <br /> * Yang Hou, Houquan Zhou, Zhenghua Li*, Yu Zhang, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. A Coarse-to-Fine Labeling Framework for Joint Word Segmentation, POS Tagging, and Constituent Parsing. Proceedings of CoNLL-2021, pp. 290–299. Punta Cana, Dominican Republic (Online), 10-11 Nov. 2021. [[文件:CoNLL_2021_yhou_official_version.pdf]]<br /> <br /> * Kun Wu, Lijie Wang, Zhenghua Li, Ao Zhang, Xinyan Xiao, Hua Wu, Min Zhang, Haifeng Wang. Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-Domain Text-to-SQL Parsing. Proceedings of EMNLP-2021, pp. 8974--8983. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP2021_camera_ready_Data_Augmentation_with_Hierarchical_SQL_to_Question_Generation_forCross_domain_Text_to_SQL_Parsing-09101500.pdf ‎]]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Rui Wang, Min Zhang. Stacked AMR Parsing with Silver Data. Proceedings of EMNLP-2021 Findings, pp. 4729--4738. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_Stacked_AMR_Parsing_with_Silver_Data.pdf]]<br /> <br /> * Ying Li, Meishan Zhang, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. APGN: Adversarial and Parameter Generation Networks for Multi-Source Cross-Domain Dependency Parsing. Proceedings of EMNLP-2021 Findings, pp. 1727–1733. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_yli_camera_ready.pdf]]<br /> <br /> * Chen Gong, Saihao Huang, Houquan Zhou, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. An In-depth Study on Internal Structure of Chinese Words. Proceedings of ACL-2021, pp. 5823–5833. Online, Virtual Event, 1-6 Aug. 2021. [[文件:2021.acl-long.452.pdf]]<br /> <br /> * Qingrong Xia, Bo Zhang, Rui Wang, Zhenghua Li*, Yue Zhang, Fei Huang, Luo Si, Min Zhang. 2021. A Unified Span-Based Approach for Opinion Mining with Syntactic Constituents. Proceedings of NAACL-2021, pp. 1795-1804. Mexico City, Mexico (Online), 6-11 June. 2021. [[文件:2021.naacl-main.144.pdf]]<br /> <br /> * Jinpeng Zhang, Baijun Ji, Nini Xiao, Xiangyu Duan*, Min Zhang, Yangbin Shi, Weihua Luo: Combining Static Word Embeddings and Contextual Representations for Bilingual Lexicon Induction, ACL 2021 Findings. [https://aclanthology.org/2021.findings-acl.260.pdf anthology]<br /> <br /> == 2020 == <br /> <br /> * Zhengqiu HE, Wenliang CHEN, Yuyi WANG, Wei ZHANG, Gaochun WANG, Min ZHANG. Improving Neural Relation Extraction with Positive and Unlabeled Learning. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), pp. 7927-7934. New York, 7-12 Feb. 2020，<br /> <br /> * 杨一帆, 马进, 王海涛, 何正球，陈文亮，张民. 基于简介文本的中文人物关系图谱属性补全与纠错. 中国科学-信息科学. V50(7) : 1003-1018(2020)<br /> <br /> * Junjie Yu, Tong Zhu, Wenliang Chen, Wei Zhang and Min Zhang. Improving Relation Extraction with Relational Paraphrase Sentences. COLING2020, pp. 1687-1698. Online, Dec. 2020[http://hlt.suda.edu.cn/images/9/96/Coling2020-junjie2073_Paper.pdf pdf]<br /> <br /> * Tong Zhu, Haitao Wang, Junjie Yu, Xiabing Zhou, Wenliang Chen, Wei Zhang and Min Zhang. Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction. COLING2020. pp. 6436-6447, Online, Dec. 2020 [https://arxiv.org/pdf/2010.16275.pdf pdf], [https://github.com/Spico197/NYT-H 数据下载@github]<br /> <br /> * Baijun JI, Zhirui ZHANG, Xiangyu DUAN, Min ZHANG, Boxing CHEN and Weihua LUO. Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Xiangyu Duan, Baijun Ji, Hao Jia, Min Tan, Min Zhang, Boxing Chen, Weihua Luo, Yue Zhang: Bilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences. The 58th Annual Meeting of the Association for Computational Linguistics (ACL-2020).<br /> <br /> * Kai SONG, Kun WANG, Heng YU, Yue ZHANG, Zhongqiang HUANG, Weihua LUO, Xiangyu DUAN and Min ZHANG. Alignment-Enhanced Transformer for Constraining NMT with Pre-Specified Translations. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Kai Song, Xiaoqing Zhou, Heng Yu, Zhongqiang Huang, Yue Zhang, Weihua Luo, Xiangyu Duan, Min Zhang: Towards Better Word Alignment in Transformer. IEEE ACM Transaction Audio Speech Language Processing (TASLP), 2020.<br /> <br /> * Huaao Zhang,Shigui Qiu, Xiangyu Duan*,Min Zhang: Token Drop mechanism for Neural Machine Translation. The International Conference on Computational Linguistics (Coling-2020) (short paper).<br /> <br /> * Chen Gong, Zhenghua Li, Qingrong Xia, Wenliang Chen and Min Zhang. Hierarchical LSTM with char-subword-word tree-structure representation for Chinese named entity recognition. Science China Information Science, 2020, 63(10):1-15. [[文件:Hierarchical_LSTM_with_char-subword-word_tree-structure_representation_for_Chinese_named_entity_recognition.pdf]]<br /> <br /> * Ying Li, Zhenghua Li* and Min Zhang. Semi-supervised Domain Adaptation for Dependency Parsing via Improved Contextualized Word Representations. Proceedings of COLING-2020. pp. 3806–3817. Barcelona, Spain (Online), 8-13 Dec. 2020.[https://www.aclweb.org/anthology/2020.coling-main.338.pdf pdf] [[文件:Liying-2020.coling-main.338.pdf]]<br /> <br /> * Qingrong Xia, Rui Wang, Zhenghua Li, Yue Zhang and Min Zhang*. Semantic Role Labeling with Heterogeneous Syntactic Knowledge. Proceedings of COLING-2020. pp. 2979-2990. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/2020.coling-main.266.pdf pdf][[文件:Xiaqingrong-2020.coling-main.266.pdf]]<br /> <br /> * Chen Gong, Zhenghua Li*, Bowei Zou and Min Zhang. Multi-grained Chinese Word Segmentation with Weakly Labeled Data. Proceedings of COLING-2020. pp. 2026–2036. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/D17-1072.pdf pdf][[文件:Gongchen-2020.coling-main.183.pdf]]<br /> <br /> * Lijie Wang, Ao Zhang, Kun Wu, Ke Sun, Zhenghua Li, Hua Wu*, Min Zhang and Haifeng Wang. DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset. Proceedings of EMNLP-2020. pp. 6923-6935. Online, 16-20 Nov. 2020. [https://www.aclweb.org/anthology/2020.emnlp-main.562.pdf pdf][[文件:2020.emnlp-main.562.pdf]]<br /> <br /> * Houquan Zhou, Yu Zhang, Zhenghua Li, and Min Zhang. Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing? Proceedings of NLPCC-2020, pp. 179--191. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo.pdf pdf]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official-w-content.pdf pdf-official-w-content]) &lt;font color=&quot;#FF0000&quot;&gt;&lt;b&gt;(best paper!)&lt;/b&gt;&lt;/font&gt; <br /> <br /> * Yu Zhao, Mingyue Zhou, Zhenghua Li, and Min Zhang. Dependency Parsing with Noisy Multi-Annotation Data. Proceedings of NLPCC-2020, pp. 120-131. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/images/e/e5/212_Final_Manuscript_%281%29.pdf pdf]）([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official-w-content.pdf pdf-official-w-content])<br /> <br /> * Yu Zhang, Houquan Zhou, Zhenghua Li. 2020. Fast and Accurate Neural CRF Constituency Parsing. Proceedings of IJCAI-2020, pp. 4046-4053. Yokohama, Japan, 11-17 Jul. 2020. [https://www.ijcai.org/Proceedings/2020/0560.pdf pdf-official] [http://hlt.suda.edu.cn/LA/papers/0560.pdf pdf] [[http://hlt.suda.edu.cn/LA/videos/V5.mp4 video(5 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V10.mp4 video(10 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V15.mp4 video(15 min version)]]<br /> <br /> * Yu Zhang, Zhenghua Li, Min Zhang. 2020. Efficient Second-Order TreeCRF for Neural Dependency Parsing. Proceedings of ACL-2020, pp. 3295-3305. Seattle, America, 5-10 Jul. 2020. ][https://www.aclweb.org/anthology/2020.acl-main.302.pdf pdf-official]] [[http://hlt.suda.edu.cn/LA/papers/2020.acl-main.302.pdf pdf]] [[http://hlt.suda.edu.cn/LA/videos/2020-12-28%2022-21-45.mp4 video]]<br /> <br /> * Bo Zhang, Yue Zhang, Rui Wang, Zhenghua Li, Min Zhang. Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks. Proceedings of ACL-2020, pp. 3249-3258. Seattle, America, 5-10 Jul. 2020. [https://www.aclweb.org/anthology/2020.acl-main.297.pdf pdf] [[文件:Zhangbo-acl2020-ppt-5-24.pdf]]<br /> <br /> == 2019 ==<br /> * Zhengqiu He, Wenliang Chen, Zhenghua Li, Wei Zhang, Hao Shao, Min Zhang. 2019. Syntax-aware Entity Representations for Neural Relation Extraction. Artificial Intelligence Journal.275(2019):602-617, October 2019.[https://doi.org/10.1016/j.artint.2019.07.004 online version]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Min Zhang. A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling, Proceedings of EMNLP-2019, pp5385-5395, HongKong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1541.pdf PDF]<br /> <br /> * Xiangyu Duan, Hongfei Yu, Mingming Yin, Min Zhang, Weihua Luo, Yue Zhang. Contrastive Attention Mechanism for Abstractive Sentence Summarization, Proceeding of EMNLP-2019, pp3035–3044, Hong Kong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1301 PDF]<br /> <br /> * Hongfei Yu, Xiaoqing Zhou, Xiangyu Duan, Min Zhang. Layer-wise De-training and Re-training for Convolutional Sequence to Sequence Machine Translation, Asian and Low-Resource Language Information Processing, Vol. 19, No. 2, Article 26[J][https://dl.acm.org/citation.cfm?id=3358414 PDF]<br /> <br /> * Xiangyu Duan, Mingming Yin, Min Zhang, Boxing Chen, Weihua Luo. Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention, Proceeding of ACL-2019, pp3162–3172, Florence, Italy, Jul 28 - Aug 2, 2019. [C] [https://www.aclweb.org/anthology/P19-1305 PDF]<br /> <br /> * Zhenghua Li, Xue Peng, Min Zhang, Rui Wang, Luo Si. 2019. Semi-supervised Domain Adaptation for Dependency Parsing. Proceedings of ACL-2019, pp. 2386-2395. Florence, Italy, 28 Jul. - 2 Aug. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua_acl19_dp_2.pdf PDF]<br /> <br /> * Kai SONG, Yue ZHANG, Heng YU, Weihua LUO, Kun WANG and Min ZHANG. Code-Switching for Enhancing NMT with Pre-Specified Translation. Proceedings of the 20th Annual Conference of the North American Chapter of the ACL (NAACL-2019), 136–144, Minneapolis, 2-7 June 2019 [C]<br /> <br /> * Meishan Zhang, Zhenghua Li, Guohong Fu, Min Zhang. 2019. Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations. Proceedings of NAACL-2019, pp. 1151-1161. Minneapolis, Minnesota, America, 2-7 Jun. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhang-naacl-2019.pdf PDF]<br /> <br /> * Ying Li, Zhenghua Li, Min Zhang, Rui Wang, Sheng Li, Luo Si. 2019. Self-attentive Biaffine Dependency Parsing. Proceedings of IJCAI-2019, pp. 5067-5073. Macao, China, 10-16 Aug. 2019 [https://www.ijcai.org/proceedings/2019/0704.pdf PDF]<br /> <br /> * Qingrong Xia, Zhenghua Li, Min Zhang, Meishan Zhang, Guohong Fu, Rui Wang, Luo Si. 2019. Syntax-aware Neural Semantic Role Labeling. Proceedings of AAAI-2019, pp. x-x. Honolulu, Hawaii, America, 27 Jan. - 1 Feb. 2019. [http://hlt.suda.edu.cn/kiro/papers/aaai19.pdf PDF]<br /> <br /> * 周俊佐, 朱宗奎, 何正球, 陈文亮, 张民. 面向人机对话意图分类的混合神经网络模型. 软件学报. 2019,30(11):3313-3325[http://www.jos.org.cn/jos/ch/reader/view_abstract.aspx?file_no=5862&amp;flag=1 PDF]<br /> <br /> == 2018 ==<br /> <br /> * Xinzhou Jiang, Bo Zhang, Zhenghua Li, Min Zhang, Sheng Li, Luo Si. Supervised Treebank Conversion: Data and Approaches. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL-2018), pp. 2706-2716. Melbourne, Australia. 15-20 Jul. 2018[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl18.pdf PDF]<br /> <br /> * Yachao Li, Junhui Li, Min Zhang. Adapted Weights for Neural Machine Translation. In Proceedings of COLING-2018, pp. 3038–3048, Santa Fe, New Mexico, USA, August 20-26, 2018[C]<br /> <br /> * Yaosheng Yang, Wenliang Chen, Zhenghua Li, Zhengqiu He and Min Zhang. Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning, Proceedings of COLING2018, pp.2159–2169, Santa Fe, New Mexico, USA, August 20-26, 2018[C] [https://github.com/rainarch/DSNER Code] [http://aclweb.org/anthology/C18-1183 PDF]<br /> <br /> * Kai Song, Yue Zhang, Min Zhang, Weihua Luo. Improved English to Russian Translation by Neural Suffix Prediction, Proceedings of AAAI-2018, pp410-417, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03615 PDF]<br /> <br /> * YaoSheng Yang, Meishan Zhang, Wenliang Chen*, Haofen Wang, Wei Zhang, Min Zhang. Adversarial Learning for Chinese NER from Crowd Annotations, Proceedings of AAAI-2018, pp1627-1634, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Zhengqiu He, Wenliang Chen*, Zhenghua Li, Meishan Zhang, Wei Zhang, Min Zhang. SEE: Syntax-aware Entity Embedding for Neural Relation Extraction, Proceedings of AAAI-2018, pp5795-5802, New Orleans, USA,Feb 2018[C] [http://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Qi Lu, YaoSheng Yang, Zhenghua Li, Wenliang Chen and Min Zhang. M-CNER: A Corpus for Chinese Named Entity Recognition in Multi-Domains, Proceedings of LREC-2018, pp4458-4461, Japan, May 2018 [http://hlt.suda.edu.cn/~zhli/papers/lrec-2018-ner.pdf PDF]<br /> <br /> == 2017 ==<br /> * Wenliang Chen, Muhua Zhu, Min Zhang, Yue Zhang, Jingbo Zhu. Improving Shift-Reduce Phrase-Structure Parsing with Constituent Boundary Information. Computational Intelligence Journal, 33(3):428-447, August 2017[J]<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen, Meishan Zhang, Guohong Fu. 2016. Coupled POS Tagging on Heterogeneous Annotations. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2017. 25(3), pp. 557-571.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua-ieee17-coupled-pos.pdf PDF]<br /> <br /> * Yue Zhang, Zhenghua Li, Jun Lang, Qingrong Xia, Min Zhang. 2017. Dependency Parsing with Partial Annotations: An Empirical Comparison. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-2017), pp. 49-58. Taiwan, Nov. 27 - Dec. 1, 2017[C] [http://aclweb.org/anthology/I/I17/I17-1006.pdf PDF]<br /> <br /> * Chen Gong, Zhenghua Li, Min Zhang, Xinzhou Jiang. 2017. Multi-Grained Chinese Word Segmentation. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP-2017), pp. 703-714. Copenhagen, Denmark, 7-11 Sept. 2017[C] [http://hlt.suda.edu.cn/~zhli/papers/chen-d17-mws.pdf PDF]<br /> <br /> == 2016 ==<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Jiwen Yang. Fast Coupled Sequence Labeling on Heterogeneous Annotations via Context-aware Pruning. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-2016), pp. 753-762. Austin, Texas, USA, 1-5 Nov. 2016[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-emnlp-2016-submission.pdf PDF]<br /> <br /> * Zhenghua Li, Min Zhang, Yue Zhang, Zhanyi Liu, Wenliang Chen, Hua Wu, Haifeng Wang. Active Learning for Dependency Parsing with Partial Annotation. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-2016), pp. 344-354. Berlin, 7-12 Aug. 2016[C] [http://hlt.suda.edu.cn/~zhli/acl-2016-resources/zhenghua-acl2016-camera-ready.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang, Xiangyu Duan. Exploiting Meta Features for Dependency Parsing and Part-of-speech Tagging. Artificial Intelligence Journal, 230(2016):173-191, January 2016[J]<br /> <br /> * Wenliang Chen, Zhenjie Zhang, Zhenghua Li, Min Zhang. Distributed Representations for Building Profiles of Users and Items from Text Reviews. In Proc. of the 26th International Conference on Computational Linguistics (COLING-2016), pp2143-2153, Osaka, 11-17 Dec. 2016[C][https://www.aclweb.org/anthology/C16-1202.pdf PDF]<br /> <br /> == 2015 ==<br /> *Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen. 2015. Coupled Sequence Labeling on Heterogeneous Annotations: POS Tagging as a Case Study. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-2015), pp. 1783-1792. Beijing, 26-31 July 2015[C] [http://aclweb.org/anthology/P/P15/P15-1172.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> == 2014 ==<br /> *Zhenghua Li, Min Zhang, Wanxiang Che, Ting Liu, Wenliang Chen. 2014. Joint Optimization for Chinese POS Tagging and Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2014. 22(1), pp. 274-286.[J] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-taslp14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Soft Cross-lingual Syntax Projection for Dependency Parsing. Proceedings of the 25th International Conference on Computational Linguistics (COLING-2014), pp. 783-793. Dublin, 23-29 Aug. 2014[C][http://hlt.suda.edu.cn/~zhli/papers/zhenghua-coling14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Ambiguity-aware Ensemble Training for Semi-supervised Dependency Parsing. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL-2014), pp. 457-467. Baltimore, 22-27 June 2014[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl14.pdf PDF] <br /> <br /> * Min ZHANG, Xiangyu Duan, Wenliang CHEN. Bayesian Constituent Context Model for Grammar Induction. IEEE/ACM Transactions on Audio, Speech and Language Processing, 22(2):531-541, 2014[J]<br /> <br /> * Xiangyu Duan, Min Zhang, Qiaoming Zhu. Synchronous Constituent Context Model for Inducing Bilingual Synchronous Structures. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp783-793, Dublin, Ireland, August 2014<br /> <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp816-826, Dublin, Ireland, August 2014<br /> <br /> == 2013 ==<br /> * Min Zhang, Wenliang Chen*, Xiangyu Duan, and Rong Zhang. Improving Graph-based Dependency Parsing Models with Dependency Language Models. IEEE Transactions on Audio, Speech and Language Processing (IEEE-TASL), Vol.21, No.11, pp2313-2323 November 2013. <br /> <br /> * Muhua Zhu, Yue Zhang, Wenliang Chen, Min Zhang, and Jingbo Zhu. Fast and Accurate Constituent Parsing. In Proc. of ACL2013, pp 434-443, Sofia, Bulgaria, August 2013.<br /> <br /> * Xiangyu Duan, Min Zhang, Wenliang Chen. Smoothing for Bracketing Induction. In Proc. of IJCAI2013, pp 2085-2091, Beijing, China, August 2013.<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang. Semi-Supervised Feature Transformation for Dependency Parsing. In Proc. of EMNLP2013, pp1303-1313, Seattle, Washington, USA, 18-21 October 2013.<br /> <br /> == 更古老 ==<br /> <br /> * 请查看各位成员的主页<br /> <br /> <br /> == 参考格式 ==<br /> 期刊格式：[作者列表]. [题目]. [期刊名], [卷号(期):起止页码], [年份][J]<br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> 会议格式：[作者列表]. [题目]. [In Proc. of 会议名], [起止页码], [地点], [会议时间][C] <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING-2014), pp816-826, Dublin, Ireland, August 2014[C]<br /> <br /> 录用格式：[作者列表]. [题目]. [期刊名/会议名], 已录用<br /> * Wenliang Chen. Feature Embedding for Dependency Parsing. CCL-2017, 已录用</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=5389 2024-02-26T07:21:42Z

<p>Xjshi：/* 最近更新 */</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://xyda.github.io/ homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 多模态跨语言短语检索，提升短语翻译性能，该项研究被COLING2024接收。
<br /> <br /> * 面向大模型机器翻译的子模(Submodular)示例选择方法，该项研究被COLING2024接收。

<br /> <br /> * 面向可定制的翻译服务，提出词汇约束消岐的神经机器翻译，该项研究被[https://aclanthology.org/2023.findings-acl.673.pdf ACL2023-Findings]接收。<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings] 接收<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> <br /> 更多信息请参看[https://xyda.github.io 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> 周文杰，Low Resource<br /> <br /> 缪思睿，Pre-training for Machine Translation<br /> <br /> 周烁，Low Resource<br /> <br /> 董川齐，Multi-Modal Machine Translation<br /> <br /> 张竹君，Machine Translation Modeling<br /> <br /> 李博，Machine Translation Structures<br /> <br /> 张誉泷，Cross Lingual Applications<br /> <br /> 张婉群，Machine Translation Modeling<br /> <br /> 杜天译，Low Resource<br /> <br /> 李扬韬，Reasoning for Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 邱石贵, Cross-lingual Applications，现就职于百度，北京<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications，现就职于腾讯，北京<br /> <br /> 章华奥, Machine Translation Applications，现就职于同花顺，杭州<br /> <br /> 王煦, Cross-lingual Applications，现就职于智慧芽，苏州<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=5388 2024-02-26T06:43:21Z

<p>Xjshi：/* 学生 */</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://xyda.github.io/ homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 多模态跨语言短语检索，提升短语翻译性能，该项研究被COLING2024接收。
<br /> <br /> * 面向大模型机器翻译的子模(Submodular)示例选择方法，该项研究被COLING2024接收。

<br /> <br /> * 面向可定制的翻译服务，提出词汇约束消岐的神经机器翻译，该项研究被[https://aclanthology.org/2023.findings-acl.673.pdf ACL2023-Findings]接收。<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings] 接收<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> 周文杰，Low Resource<br /> <br /> 缪思睿，Pre-training for Machine Translation<br /> <br /> 周烁，Low Resource<br /> <br /> 董川齐，Multi-Modal Machine Translation<br /> <br /> 张竹君，Machine Translation Modeling<br /> <br /> 李博，Machine Translation Structures<br /> <br /> 张誉泷，Cross Lingual Applications<br /> <br /> 张婉群，Machine Translation Modeling<br /> <br /> 杜天译，Low Resource<br /> <br /> 李扬韬，Reasoning for Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 邱石贵, Cross-lingual Applications，现就职于百度，北京<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications，现就职于腾讯，北京<br /> <br /> 章华奥, Machine Translation Applications，现就职于同花顺，杭州<br /> <br /> 王煦, Cross-lingual Applications，现就职于智慧芽，苏州<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=5386 2024-02-26T06:38:35Z

<p>Xjshi：/* 最近更新 */</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://xyda.github.io/ homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 多模态跨语言短语检索，提升短语翻译性能，该项研究被COLING2024接收。
<br /> <br /> * 面向大模型机器翻译的子模(Submodular)示例选择方法，该项研究被COLING2024接收。

<br /> <br /> * 面向可定制的翻译服务，提出词汇约束消岐的神经机器翻译，该项研究被[https://aclanthology.org/2023.findings-acl.673.pdf ACL2023-Findings]接收。<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings] 接收<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=5384 2024-02-26T06:37:25Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://xyda.github.io/ homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 多模态跨语言短语检索，提升短语翻译性能，该项研究被COLING2024接收。
<br /> <br /> * 面向大模型机器翻译的子模(Submodular)示例选择方法，该项研究被COLING2024接收。

<br /> <br /> * 面向可定制的翻译服务，提出词汇约束消岐的神经机器翻译，该项研究被[https://aclanthology.org/2023.findings-acl.673.pdf ACL2023-Findings]接收。<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings] 接收<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好的约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4919 2022-11-11T04:04:57Z

<p>Xjshi：撤销Xjshi（讨论）的版本3056</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://xyda.github.io/ homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings] 接收<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好的约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4918 2022-11-11T04:03:28Z

<p>Xjshi：撤销Xjshi（讨论）的版本4224</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://xyda.github.io/ homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings] 接收<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4917 2022-11-11T03:43:00Z

<p>Xjshi：撤销Xjshi（讨论）的版本4916</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://xyda.github.io/ homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings] 接收<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4916 2022-11-11T03:41:15Z

<p>Xjshi：页面内容被替换为“[https://xyda.github.io/ 请参见个人主页]”</p> <hr /> <div>[https://xyda.github.io/ 请参见个人主页]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4915 2022-11-11T01:49:41Z

<p>Xjshi：/* 最近更新 */</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://xyda.github.io/ homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings] 接收<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4914 2022-11-11T01:46:19Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://xyda.github.io/ homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4913 2022-11-11T01:42:55Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://web.suda.edu.cn/xiangyuduan/ 请参见个人主页]<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Members&diff=4884 2022-07-04T07:36:34Z

<p>Xjshi：/* 毕业学生(毕业第一次工作去向) */</p> <hr /> <div><br /> == 在校老师 ==<br /> * [[Faculty|English Version]]<br /> * 教师：[https://zhangminsuda.github.io/ 张民]、付国宏、[[Wenliang|陈文亮]]、[http://hlt.suda.edu.cn/index.php/%E6%AE%B5%E6%B9%98%E7%85%9C 段湘煜]、[http://hlt.suda.edu.cn/~zhli/ 李正华]、[http://web.suda.edu.cn/zhouxiabing/ 周夏冰]、[http://web.suda.edu.cn/cm/ 曹敏]、[https://lijuntaopku.github.io/ 李俊涛]、冯思为、曹自强<br /> * 科研助理：[[仇慧敏]]<br /> <br /> == 在校学生（[http://hlt.suda.edu.cn/index.php/Stu_candidates 招生说明]）==<br /> <br /> * 2017博：[[郁俊杰]]、(1)<br /> <br /> * 2019博：贾昊、余南 (2)<br /> <br /> * 2020博：刘振华、梁晓波、张建新、刘亚慧 (4)<br /> <br /> * 2021博：朱桐、周厚全、张宇（3）<br /> <br /> * 2022博：侯洋、周仕林（2）<br /> <br /> <br /> * 2020硕：张智林、张国梁、陈跃鹤、张飞宇、周沛、侯洋（转博）、李帅克、周仕林（转博）、李嘉诚、李扬、刘泽洋、张金鹏、金畅、肖妮妮、段仁翀、张冕、丁家杰 （17）<br /> <br /> * 2021硕：谈川源、任俊飞、余子健、项健翔、刘资蕴、章岳、黄赛豪、窦晨晖、严福康、崔秀莲、张磊、周烁、张竹君、董川奇、周文杰、缪思睿、杨帆、王泽、高晓倩 （19）<br /> <br /> * 2022硕：汤添文、吴孟松、邵文彪、辜仰淦、蒋浩辰、刘雨萌、马溪、胡宫朕、姚煜铖、王凯悦、张誉泷、李博、张婉群（13）<br /> <br /> == 访问学者/学生==<br /> * 访问学者：秦彦霞（东华大学讲师，哈工大博士）<br /> * 访问学生：杨明明（哈工大博士生）<br /> <br /> == 毕业学生(毕业第一次工作去向) ==<br /> <br /> === 博士 ===<br /> <br /> * 2022毕业博：[http://hlt.suda.edu.cn/gongchen/ 龚晨]（苏州大学）、[http://hlt.suda.edu.cn/kiro 夏庆荣]（华为）、[[李英]]（昆明理工大学）、李亚超（西北民族大学）、宋楷（字节跳动）<br /> <br /> * 2018毕业博：王星（腾讯AILab）<br /> <br /> === 硕士 ===<br /> * 2022毕业硕：贾永辉（字节）、[https://spico197.github.io/ 朱桐]（转博）、刘振华（转博）、沈嘉钰、杨浩苹（思必驰）、周厚全（转博）、周明月、贾浩（腾讯）、章华奥（同花顺）、王煦（智慧芽）、吴世龙、邱石贵（百度）、张世奇（VIVO）、陈楠（工行）、陈晨（美团）、李子仪（交行）（16）<br /> <br /> * 2021毕业硕：方晔玮（百度）、王海涛（华为）、马进（美团）、张鹏举（腾讯）、王铭涛（苏大）、蒋炜（华为）、刘亚慧（苏大转博）、陆凯华（上海银行）、吴锟（百度）、张宇（苏大转博）、季佰军（腾讯）、史小静（搜狗）、宁秋怡（联通）、肖康(网易)（14）<br /> <br /> * 2020毕业硕：张栋（同花顺）、杨一帆（思必驰）、朱宗奎（华为）、周俊佐（阿里巴巴）、郁圣卫、黄德朋（小红书）、江心舟、彭雪（移动苏州）、章波（阿里巴巴）、谭敏（华为）、周孝青（OPPO）、殷明明（搜狗）、俞鸿飞（美团） (13)<br /> <br /> * 2019毕业硕：何正球（美团）、杨耀晟（阿里巴巴）、郭丽娟（狗尾草）、孙佳伟（苏州微软）、朱运（搜狗）、汪琪（深圳招商银行总行）、王坤（杭州搜狗研究院）、龚晨（苏大读博）、夏庆荣（苏大读博） (9)<br /> <br /> * 2018毕业硕：陈伟（爱奇艺）、凡子威（搜狗）、卢奇（美团）、张月（阿里巴巴） (4)<br /> <br /> * 2017毕业硕：巢佳媛（阿里巴巴）、陈志鹏（百度公司）、龚慧敏（同程公司）、郁俊杰（苏大读博）(4)<br /> <br /> * 2016毕业硕：马春平（阿里巴巴）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Members&diff=4883 2022-07-04T07:35:08Z

<p>Xjshi：/* 在校学生（招生说明） */</p> <hr /> <div><br /> == 在校老师 ==<br /> * [[Faculty|English Version]]<br /> * 教师：[https://zhangminsuda.github.io/ 张民]、付国宏、[[Wenliang|陈文亮]]、[http://hlt.suda.edu.cn/index.php/%E6%AE%B5%E6%B9%98%E7%85%9C 段湘煜]、[http://hlt.suda.edu.cn/~zhli/ 李正华]、[http://web.suda.edu.cn/zhouxiabing/ 周夏冰]、[http://web.suda.edu.cn/cm/ 曹敏]、[https://lijuntaopku.github.io/ 李俊涛]、冯思为、曹自强<br /> * 科研助理：[[仇慧敏]]<br /> <br /> == 在校学生（[http://hlt.suda.edu.cn/index.php/Stu_candidates 招生说明]）==<br /> <br /> * 2017博：[[郁俊杰]]、(1)<br /> <br /> * 2019博：贾昊、余南 (2)<br /> <br /> * 2020博：刘振华、梁晓波、张建新、刘亚慧 (4)<br /> <br /> * 2021博：朱桐、周厚全、张宇（3）<br /> <br /> * 2022博：侯洋、周仕林（2）<br /> <br /> <br /> * 2020硕：张智林、张国梁、陈跃鹤、张飞宇、周沛、侯洋（转博）、李帅克、周仕林（转博）、李嘉诚、李扬、刘泽洋、张金鹏、金畅、肖妮妮、段仁翀、张冕、丁家杰 （17）<br /> <br /> * 2021硕：谈川源、任俊飞、余子健、项健翔、刘资蕴、章岳、黄赛豪、窦晨晖、严福康、崔秀莲、张磊、周烁、张竹君、董川奇、周文杰、缪思睿、杨帆、王泽、高晓倩 （19）<br /> <br /> * 2022硕：汤添文、吴孟松、邵文彪、辜仰淦、蒋浩辰、刘雨萌、马溪、胡宫朕、姚煜铖、王凯悦、张誉泷、李博、张婉群（13）<br /> <br /> == 访问学者/学生==<br /> * 访问学者：秦彦霞（东华大学讲师，哈工大博士）<br /> * 访问学生：杨明明（哈工大博士生）<br /> <br /> == 毕业学生(毕业第一次工作去向) ==<br /> <br /> === 博士 ===<br /> <br /> * 2022毕业博：[http://hlt.suda.edu.cn/gongchen/ 龚晨]（苏州大学）、[http://hlt.suda.edu.cn/kiro 夏庆荣]（华为）、[[李英]]（昆明理工大学）、李亚超（西北民族大学）、宋楷（字节跳动）<br /> <br /> * 2018毕业博：王星（腾讯AILab）<br /> <br /> === 硕士 ===<br /> * 2022毕业硕：贾永辉（字节）、[https://spico197.github.io/ 朱桐]（转博）、刘振华（转博）、沈嘉钰、杨浩苹（思必驰）、周厚全（转博）、周明月、贾浩、章华奥、王煦、吴世龙、邱石贵、张世奇（VIVO）、陈楠（工行）、陈晨（美团）、李子仪（交行）（16）<br /> <br /> * 2021毕业硕：方晔玮（百度）、王海涛（华为）、马进（美团）、张鹏举（腾讯）、王铭涛（苏大）、蒋炜（华为）、刘亚慧（苏大转博）、陆凯华（上海银行）、吴锟（百度）、张宇（苏大转博）、季佰军（腾讯）、史小静（搜狗）、宁秋怡（联通）、肖康(网易)（14）<br /> <br /> * 2020毕业硕：张栋（同花顺）、杨一帆（思必驰）、朱宗奎（华为）、周俊佐（阿里巴巴）、郁圣卫、黄德朋（小红书）、江心舟、彭雪（移动苏州）、章波（阿里巴巴）、谭敏（华为）、周孝青（OPPO）、殷明明（搜狗）、俞鸿飞（美团） (13)<br /> <br /> * 2019毕业硕：何正球（美团）、杨耀晟（阿里巴巴）、郭丽娟（狗尾草）、孙佳伟（苏州微软）、朱运（搜狗）、汪琪（深圳招商银行总行）、王坤（杭州搜狗研究院）、龚晨（苏大读博）、夏庆荣（苏大读博） (9)<br /> <br /> * 2018毕业硕：陈伟（爱奇艺）、凡子威（搜狗）、卢奇（美团）、张月（阿里巴巴） (4)<br /> <br /> * 2017毕业硕：巢佳媛（阿里巴巴）、陈志鹏（百度公司）、龚慧敏（同程公司）、郁俊杰（苏大读博）(4)<br /> <br /> * 2016毕业硕：马春平（阿里巴巴）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Members&diff=4882 2022-07-04T07:34:43Z

<p>Xjshi：/* 在校学生（招生说明） */</p> <hr /> <div><br /> == 在校老师 ==<br /> * [[Faculty|English Version]]<br /> * 教师：[https://zhangminsuda.github.io/ 张民]、付国宏、[[Wenliang|陈文亮]]、[http://hlt.suda.edu.cn/index.php/%E6%AE%B5%E6%B9%98%E7%85%9C 段湘煜]、[http://hlt.suda.edu.cn/~zhli/ 李正华]、[http://web.suda.edu.cn/zhouxiabing/ 周夏冰]、[http://web.suda.edu.cn/cm/ 曹敏]、[https://lijuntaopku.github.io/ 李俊涛]、冯思为、曹自强<br /> * 科研助理：[[仇慧敏]]<br /> <br /> == 在校学生（[http://hlt.suda.edu.cn/index.php/Stu_candidates 招生说明]）==<br /> <br /> * 2017博：[[郁俊杰]]、(1)<br /> <br /> * 2019博：贾昊、余南 (2)<br /> <br /> * 2020博：刘振华、梁晓波、张建新、刘亚慧 (4)<br /> <br /> * 2021博：朱桐、周厚全、张宇（3）<br /> <br /> * 2022博：侯洋、周仕林（2）<br /> <br /> <br /> * 2020硕：张智林、张国梁、陈跃鹤、张飞宇、周沛、侯洋（转博）、李帅克、周仕林（转博）、李嘉诚、李扬、刘泽洋、张金鹏、金畅、肖妮妮、段仁翀、张冕、丁家杰 （17）<br /> <br /> * 2021硕：谈川源、任俊飞、余子健、项健翔、刘资蕴、章岳、黄赛豪、窦晨晖、严福康、崔秀莲、张磊、周烁、张竹君、董川奇、周文杰、缪思睿、杨帆、王泽、高晓倩 （19）<br /> <br /> * 2022硕：汤添文、吴孟松、邵文彪、辜仰淦、蒋浩辰、刘雨萌、马溪、胡宫朕、姚煜铖、王凯悦、张誉泷、李博、张婉群（10）<br /> <br /> == 访问学者/学生==<br /> * 访问学者：秦彦霞（东华大学讲师，哈工大博士）<br /> * 访问学生：杨明明（哈工大博士生）<br /> <br /> == 毕业学生(毕业第一次工作去向) ==<br /> <br /> === 博士 ===<br /> <br /> * 2022毕业博：[http://hlt.suda.edu.cn/gongchen/ 龚晨]（苏州大学）、[http://hlt.suda.edu.cn/kiro 夏庆荣]（华为）、[[李英]]（昆明理工大学）、李亚超（西北民族大学）、宋楷（字节跳动）<br /> <br /> * 2018毕业博：王星（腾讯AILab）<br /> <br /> === 硕士 ===<br /> * 2022毕业硕：贾永辉（字节）、[https://spico197.github.io/ 朱桐]（转博）、刘振华（转博）、沈嘉钰、杨浩苹（思必驰）、周厚全（转博）、周明月、贾浩、章华奥、王煦、吴世龙、邱石贵、张世奇（VIVO）、陈楠（工行）、陈晨（美团）、李子仪（交行）（16）<br /> <br /> * 2021毕业硕：方晔玮（百度）、王海涛（华为）、马进（美团）、张鹏举（腾讯）、王铭涛（苏大）、蒋炜（华为）、刘亚慧（苏大转博）、陆凯华（上海银行）、吴锟（百度）、张宇（苏大转博）、季佰军（腾讯）、史小静（搜狗）、宁秋怡（联通）、肖康(网易)（14）<br /> <br /> * 2020毕业硕：张栋（同花顺）、杨一帆（思必驰）、朱宗奎（华为）、周俊佐（阿里巴巴）、郁圣卫、黄德朋（小红书）、江心舟、彭雪（移动苏州）、章波（阿里巴巴）、谭敏（华为）、周孝青（OPPO）、殷明明（搜狗）、俞鸿飞（美团） (13)<br /> <br /> * 2019毕业硕：何正球（美团）、杨耀晟（阿里巴巴）、郭丽娟（狗尾草）、孙佳伟（苏州微软）、朱运（搜狗）、汪琪（深圳招商银行总行）、王坤（杭州搜狗研究院）、龚晨（苏大读博）、夏庆荣（苏大读博） (9)<br /> <br /> * 2018毕业硕：陈伟（爱奇艺）、凡子威（搜狗）、卢奇（美团）、张月（阿里巴巴） (4)<br /> <br /> * 2017毕业硕：巢佳媛（阿里巴巴）、陈志鹏（百度公司）、龚慧敏（同程公司）、郁俊杰（苏大读博）(4)<br /> <br /> * 2016毕业硕：马春平（阿里巴巴）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Papers&diff=4877 2022-06-27T07:34:49Z

<p>Xjshi：/* 2021 */</p> <hr /> <div>文章(格式见页尾)包括：<br /> * xACL(ACL/NAACL/EACL/AACL) EMNLP IJCAI AAAI COLING IJCNLP NLPCC<br /> * CCF-A/B Journal/Conference<br /> * SCI Journal<br /> * 软件学报/计算机学报/中国科学<br /> <br /> == [http://hlt.suda.edu.cn/index.php/Papers-details 论文摘要等信息] ==<br /> <br /> == 最新录用 ==<br /> <br /> == 2022 ==<br /> <br /> <br /> * Yahui Liu, Haoping Yang, Chen Gong*, Qingrong Xia, Zhenghua Li, Min Zhang. 2022. MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset. In '''NAACL'''. [http://arxiv.org/abs/2205.06703 arxiv]<br /> * Yue Zhang, Zhenghua Li*, Zuyi Bao, Jiacheng Li, Bo Zhang, Chen Li, Fei Huang, Min Zhang. 2022. MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction. In '''NAACL'''. [https://arxiv.org/abs/2204.10994 arxiv]<br /> * Ying Li, Shuaike Li, Min Zhang. 2022. Semi-supervised Domain Adaptation for Dependency Parsing with Dynamic Matching Network. In '''ACL 2022'', pages 1035--1045. [https://aclanthology.org/2022.acl-long.74.pdf official-pdf] [http://hlt.suda.edu.cn/index.php/%E6%96%87%E4%BB%B6:Liying_ACL2022_camera_ready.pdf camera ready pdf] [https://underline.io/lecture/52551-long-semi-supervised-domain-adaptation-for-dependency-parsing-with-dynamic-matching-network video].<br /> * Houquan Zhou, Yang Li, Zhenghua Li, and Min Zhang. 2022. Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging. In Findings of the Association for Computational Linguistics: ACL 2022, pages 3276–3290, Dublin, Ireland. Association for Computational Linguistics. [http://hlt.suda.edu.cn/LA/papers/acl-findings-hqzhou-bridging.pdf pdf] [https://arxiv.org/pdf/2203.10315 camera ready pdf] [https://aclanthology.org/2022.findings-acl.259.pdf offcial pdf] [https://underline.io/lecture/49965-findings-bridging-pre-trained-language-models-and-hand-crafted-features-for-unsupervised-pos-tagging video]<br /> * Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Yuan, Min Zhang. Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph. IJCAI. 2022<br /> <br /> == 2021 ==<br /> <br /> * Yang Hou, Houquan Zhou, Zhenghua Li*, Yu Zhang, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. A Coarse-to-Fine Labeling Framework for Joint Word Segmentation, POS Tagging, and Constituent Parsing. Proceedings of CoNLL-2021, pp. 290–299. Punta Cana, Dominican Republic (Online), 10-11 Nov. 2021. [[文件:CoNLL_2021_yhou_official_version.pdf]]<br /> <br /> * Kun Wu, Lijie Wang, Zhenghua Li, Ao Zhang, Xinyan Xiao, Hua Wu, Min Zhang, Haifeng Wang. Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-Domain Text-to-SQL Parsing. Proceedings of EMNLP-2021, pp. 8974--8983. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP2021_camera_ready_Data_Augmentation_with_Hierarchical_SQL_to_Question_Generation_forCross_domain_Text_to_SQL_Parsing-09101500.pdf ‎]]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Rui Wang, Min Zhang. Stacked AMR Parsing with Silver Data. Proceedings of EMNLP-2021 Findings, pp. 4729--4738. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_Stacked_AMR_Parsing_with_Silver_Data.pdf]]<br /> <br /> * Ying Li, Meishan Zhang, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. APGN: Adversarial and Parameter Generation Networks for Multi-Source Cross-Domain Dependency Parsing. Proceedings of EMNLP-2021 Findings, pp. 1727–1733. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_yli_camera_ready.pdf]]<br /> <br /> * Chen Gong, Saihao Huang, Houquan Zhou, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. An In-depth Study on Internal Structure of Chinese Words. Proceedings of ACL-2021, pp. 5823–5833. Online, Virtual Event, 1-6 Aug. 2021. [[文件:2021.acl-long.452.pdf]]<br /> <br /> * Qingrong Xia, Bo Zhang, Rui Wang, Zhenghua Li*, Yue Zhang, Fei Huang, Luo Si, Min Zhang. 2021. A Unified Span-Based Approach for Opinion Mining with Syntactic Constituents. Proceedings of NAACL-2021, pp. 1795-1804. Mexico City, Mexico (Online), 6-11 June. 2021. [[文件:2021.naacl-main.144.pdf]]<br /> <br /> * Jinpeng Zhang, Baijun Ji, Nini Xiao, Xiangyu Duan*, Min Zhang, Yangbin Shi, Weihua Luo: Combining Static Word Embeddings and Contextual Representations for Bilingual Lexicon Induction, ACL 2021 Findings. [https://aclanthology.org/2021.findings-acl.260.pdf anthology]<br /> <br /> == 2020 == <br /> <br /> * Zhengqiu HE, Wenliang CHEN, Yuyi WANG, Wei ZHANG, Gaochun WANG, Min ZHANG. Improving Neural Relation Extraction with Positive and Unlabeled Learning. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), pp. 7927-7934. New York, 7-12 Feb. 2020，<br /> <br /> * 杨一帆, 马进, 王海涛, 何正球，陈文亮，张民. 基于简介文本的中文人物关系图谱属性补全与纠错. 中国科学-信息科学. V50(7) : 1003-1018(2020)<br /> <br /> * Junjie Yu, Tong Zhu, Wenliang Chen, Wei Zhang and Min Zhang. Improving Relation Extraction with Relational Paraphrase Sentences. COLING2020, pp. 1687-1698. Online, Dec. 2020[http://hlt.suda.edu.cn/images/9/96/Coling2020-junjie2073_Paper.pdf pdf]<br /> <br /> * Tong Zhu, Haitao Wang, Junjie Yu, Xiabing Zhou, Wenliang Chen, Wei Zhang and Min Zhang. Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction. COLING2020. pp. 6436-6447, Online, Dec. 2020 [https://arxiv.org/pdf/2010.16275.pdf pdf], [https://github.com/Spico197/NYT-H 数据下载@github]<br /> <br /> * Baijun JI, Zhirui ZHANG, Xiangyu DUAN, Min ZHANG, Boxing CHEN and Weihua LUO. Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Xiangyu Duan, Baijun Ji, Hao Jia, Min Tan, Min Zhang, Boxing Chen, Weihua Luo, Yue Zhang: Bilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences. The 58th Annual Meeting of the Association for Computational Linguistics (ACL-2020).<br /> <br /> * Kai SONG, Kun WANG, Heng YU, Yue ZHANG, Zhongqiang HUANG, Weihua LUO, Xiangyu DUAN and Min ZHANG. Alignment-Enhanced Transformer for Constraining NMT with Pre-Specified Translations. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Kai Song, Xiaoqing Zhou, Heng Yu, Zhongqiang Huang, Yue Zhang, Weihua Luo, Xiangyu Duan, Min Zhang: Towards Better Word Alignment in Transformer. IEEE ACM Transaction Audio Speech Language Processing (TASLP), 2020.<br /> <br /> * Huaao Zhang,Shigui Qiu, Xiangyu Duan*,Min Zhang: Token Drop mechanism for Neural Machine Translation. The International Conference on Computational Linguistics (Coling-2020) (short paper).<br /> <br /> * Chen Gong, Zhenghua Li, Qingrong Xia, Wenliang Chen and Min Zhang. Hierarchical LSTM with char-subword-word tree-structure representation for Chinese named entity recognition. Science China Information Science, 2020, 63(10):1-15. [[文件:Hierarchical_LSTM_with_char-subword-word_tree-structure_representation_for_Chinese_named_entity_recognition.pdf]]<br /> <br /> * Ying Li, Zhenghua Li* and Min Zhang. Semi-supervised Domain Adaptation for Dependency Parsing via Improved Contextualized Word Representations. Proceedings of COLING-2020. pp. 3806–3817. Barcelona, Spain (Online), 8-13 Dec. 2020.[https://www.aclweb.org/anthology/2020.coling-main.338.pdf pdf] [[文件:Liying-2020.coling-main.338.pdf]]<br /> <br /> * Qingrong Xia, Rui Wang, Zhenghua Li, Yue Zhang and Min Zhang*. Semantic Role Labeling with Heterogeneous Syntactic Knowledge. Proceedings of COLING-2020. pp. 2979-2990. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/2020.coling-main.266.pdf pdf][[文件:Xiaqingrong-2020.coling-main.266.pdf]]<br /> <br /> * Chen Gong, Zhenghua Li*, Bowei Zou and Min Zhang. Multi-grained Chinese Word Segmentation with Weakly Labeled Data. Proceedings of COLING-2020. pp. 2026–2036. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/D17-1072.pdf pdf][[文件:Gongchen-2020.coling-main.183.pdf]]<br /> <br /> * Lijie Wang, Ao Zhang, Kun Wu, Ke Sun, Zhenghua Li, Hua Wu*, Min Zhang and Haifeng Wang. DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset. Proceedings of EMNLP-2020. pp. 6923-6935. Online, 16-20 Nov. 2020. [https://www.aclweb.org/anthology/2020.emnlp-main.562.pdf pdf][[文件:2020.emnlp-main.562.pdf]]<br /> <br /> * Houquan Zhou, Yu Zhang, Zhenghua Li, and Min Zhang. Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing? Proceedings of NLPCC-2020, pp. 179--191. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo.pdf pdf]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official-w-content.pdf pdf-official-w-content]) &lt;font color=&quot;#FF0000&quot;&gt;&lt;b&gt;(best paper!)&lt;/b&gt;&lt;/font&gt; <br /> <br /> * Yu Zhao, Mingyue Zhou, Zhenghua Li, and Min Zhang. Dependency Parsing with Noisy Multi-Annotation Data. Proceedings of NLPCC-2020, pp. 120-131. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/images/e/e5/212_Final_Manuscript_%281%29.pdf pdf]）([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official-w-content.pdf pdf-official-w-content])<br /> <br /> * Yu Zhang, Houquan Zhou, Zhenghua Li. 2020. Fast and Accurate Neural CRF Constituency Parsing. Proceedings of IJCAI-2020, pp. 4046-4053. Yokohama, Japan, 11-17 Jul. 2020. [https://www.ijcai.org/Proceedings/2020/0560.pdf pdf-official] [http://hlt.suda.edu.cn/LA/papers/0560.pdf pdf] [[http://hlt.suda.edu.cn/LA/videos/V5.mp4 video(5 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V10.mp4 video(10 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V15.mp4 video(15 min version)]]<br /> <br /> * Yu Zhang, Zhenghua Li, Min Zhang. 2020. Efficient Second-Order TreeCRF for Neural Dependency Parsing. Proceedings of ACL-2020, pp. 3295-3305. Seattle, America, 5-10 Jul. 2020. ][https://www.aclweb.org/anthology/2020.acl-main.302.pdf pdf-official]] [[http://hlt.suda.edu.cn/LA/papers/2020.acl-main.302.pdf pdf]] [[http://hlt.suda.edu.cn/LA/videos/2020-12-28%2022-21-45.mp4 video]]<br /> <br /> * Bo Zhang, Yue Zhang, Rui Wang, Zhenghua Li, Min Zhang. Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks. Proceedings of ACL-2020, pp. 3249-3258. Seattle, America, 5-10 Jul. 2020. [https://www.aclweb.org/anthology/2020.acl-main.297.pdf pdf] [[文件:Zhangbo-acl2020-ppt-5-24.pdf]]<br /> <br /> == 2019 ==<br /> * Zhengqiu He, Wenliang Chen, Zhenghua Li, Wei Zhang, Hao Shao, Min Zhang. 2019. Syntax-aware Entity Representations for Neural Relation Extraction. Artificial Intelligence Journal.275(2019):602-617, October 2019.[https://doi.org/10.1016/j.artint.2019.07.004 online version]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Min Zhang. A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling, Proceedings of EMNLP-2019, pp5385-5395, HongKong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1541.pdf PDF]<br /> <br /> * Xiangyu Duan, Hongfei Yu, Mingming Yin, Min Zhang, Weihua Luo, Yue Zhang. Contrastive Attention Mechanism for Abstractive Sentence Summarization, Proceeding of EMNLP-2019, pp3035–3044, Hong Kong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1301 PDF]<br /> <br /> * Hongfei Yu, Xiaoqing Zhou, Xiangyu Duan, Min Zhang. Layer-wise De-training and Re-training for Convolutional Sequence to Sequence Machine Translation, Asian and Low-Resource Language Information Processing, Vol. 19, No. 2, Article 26[J][https://dl.acm.org/citation.cfm?id=3358414 PDF]<br /> <br /> * Xiangyu Duan, Mingming Yin, Min Zhang, Boxing Chen, Weihua Luo. Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention, Proceeding of ACL-2019, pp3162–3172, Florence, Italy, Jul 28 - Aug 2, 2019. [C] [https://www.aclweb.org/anthology/P19-1305 PDF]<br /> <br /> * Zhenghua Li, Xue Peng, Min Zhang, Rui Wang, Luo Si. 2019. Semi-supervised Domain Adaptation for Dependency Parsing. Proceedings of ACL-2019, pp. 2386-2395. Florence, Italy, 28 Jul. - 2 Aug. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua_acl19_dp_2.pdf PDF]<br /> <br /> * Kai SONG, Yue ZHANG, Heng YU, Weihua LUO, Kun WANG and Min ZHANG. Code-Switching for Enhancing NMT with Pre-Specified Translation. Proceedings of the 20th Annual Conference of the North American Chapter of the ACL (NAACL-2019), 136–144, Minneapolis, 2-7 June 2019 [C]<br /> <br /> * Meishan Zhang, Zhenghua Li, Guohong Fu, Min Zhang. 2019. Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations. Proceedings of NAACL-2019, pp. 1151-1161. Minneapolis, Minnesota, America, 2-7 Jun. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhang-naacl-2019.pdf PDF]<br /> <br /> * Ying Li, Zhenghua Li, Min Zhang, Rui Wang, Sheng Li, Luo Si. 2019. Self-attentive Biaffine Dependency Parsing. Proceedings of IJCAI-2019, pp. 5067-5073. Macao, China, 10-16 Aug. 2019 [https://www.ijcai.org/proceedings/2019/0704.pdf PDF]<br /> <br /> * Qingrong Xia, Zhenghua Li, Min Zhang, Meishan Zhang, Guohong Fu, Rui Wang, Luo Si. 2019. Syntax-aware Neural Semantic Role Labeling. Proceedings of AAAI-2019, pp. x-x. Honolulu, Hawaii, America, 27 Jan. - 1 Feb. 2019. [http://hlt.suda.edu.cn/kiro/papers/aaai19.pdf PDF]<br /> <br /> * 周俊佐, 朱宗奎, 何正球, 陈文亮, 张民. 面向人机对话意图分类的混合神经网络模型. 软件学报. 2019,30(11):3313-3325[http://www.jos.org.cn/jos/ch/reader/view_abstract.aspx?file_no=5862&amp;flag=1 PDF]<br /> <br /> == 2018 ==<br /> <br /> * Xinzhou Jiang, Bo Zhang, Zhenghua Li, Min Zhang, Sheng Li, Luo Si. Supervised Treebank Conversion: Data and Approaches. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL-2018), pp. 2706-2716. Melbourne, Australia. 15-20 Jul. 2018[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl18.pdf PDF]<br /> <br /> * Yachao Li, Junhui Li, Min Zhang. Adapted Weights for Neural Machine Translation. In Proceedings of COLING-2018, pp. 3038–3048, Santa Fe, New Mexico, USA, August 20-26, 2018[C]<br /> <br /> * Yaosheng Yang, Wenliang Chen, Zhenghua Li, Zhengqiu He and Min Zhang. Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning, Proceedings of COLING2018, pp.2159–2169, Santa Fe, New Mexico, USA, August 20-26, 2018[C] [https://github.com/rainarch/DSNER Code] [http://aclweb.org/anthology/C18-1183 PDF]<br /> <br /> * Kai Song, Yue Zhang, Min Zhang, Weihua Luo. Improved English to Russian Translation by Neural Suffix Prediction, Proceedings of AAAI-2018, pp410-417, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03615 PDF]<br /> <br /> * YaoSheng Yang, Meishan Zhang, Wenliang Chen*, Haofen Wang, Wei Zhang, Min Zhang. Adversarial Learning for Chinese NER from Crowd Annotations, Proceedings of AAAI-2018, pp1627-1634, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Zhengqiu He, Wenliang Chen*, Zhenghua Li, Meishan Zhang, Wei Zhang, Min Zhang. SEE: Syntax-aware Entity Embedding for Neural Relation Extraction, Proceedings of AAAI-2018, pp5795-5802, New Orleans, USA,Feb 2018[C] [http://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Qi Lu, YaoSheng Yang, Zhenghua Li, Wenliang Chen and Min Zhang. M-CNER: A Corpus for Chinese Named Entity Recognition in Multi-Domains, Proceedings of LREC-2018, pp4458-4461, Japan, May 2018 [http://hlt.suda.edu.cn/~zhli/papers/lrec-2018-ner.pdf PDF]<br /> <br /> == 2017 ==<br /> * Wenliang Chen, Muhua Zhu, Min Zhang, Yue Zhang, Jingbo Zhu. Improving Shift-Reduce Phrase-Structure Parsing with Constituent Boundary Information. Computational Intelligence Journal, 33(3):428-447, August 2017[J]<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen, Meishan Zhang, Guohong Fu. 2016. Coupled POS Tagging on Heterogeneous Annotations. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2017. 25(3), pp. 557-571.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua-ieee17-coupled-pos.pdf PDF]<br /> <br /> * Yue Zhang, Zhenghua Li, Jun Lang, Qingrong Xia, Min Zhang. 2017. Dependency Parsing with Partial Annotations: An Empirical Comparison. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-2017), pp. 49-58. Taiwan, Nov. 27 - Dec. 1, 2017[C] [http://aclweb.org/anthology/I/I17/I17-1006.pdf PDF]<br /> <br /> * Chen Gong, Zhenghua Li, Min Zhang, Xinzhou Jiang. 2017. Multi-Grained Chinese Word Segmentation. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP-2017), pp. 703-714. Copenhagen, Denmark, 7-11 Sept. 2017[C] [http://hlt.suda.edu.cn/~zhli/papers/chen-d17-mws.pdf PDF]<br /> <br /> == 2016 ==<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Jiwen Yang. Fast Coupled Sequence Labeling on Heterogeneous Annotations via Context-aware Pruning. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-2016), pp. 753-762. Austin, Texas, USA, 1-5 Nov. 2016[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-emnlp-2016-submission.pdf PDF]<br /> <br /> * Zhenghua Li, Min Zhang, Yue Zhang, Zhanyi Liu, Wenliang Chen, Hua Wu, Haifeng Wang. Active Learning for Dependency Parsing with Partial Annotation. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-2016), pp. 344-354. Berlin, 7-12 Aug. 2016[C] [http://hlt.suda.edu.cn/~zhli/acl-2016-resources/zhenghua-acl2016-camera-ready.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang, Xiangyu Duan. Exploiting Meta Features for Dependency Parsing and Part-of-speech Tagging. Artificial Intelligence Journal, 230(2016):173-191, January 2016[J]<br /> <br /> * Wenliang Chen, Zhenjie Zhang, Zhenghua Li, Min Zhang. Distributed Representations for Building Profiles of Users and Items from Text Reviews. In Proc. of the 26th International Conference on Computational Linguistics (COLING-2016), pp2143-2153, Osaka, 11-17 Dec. 2016[C][https://www.aclweb.org/anthology/C16-1202.pdf PDF]<br /> <br /> == 2015 ==<br /> *Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen. 2015. Coupled Sequence Labeling on Heterogeneous Annotations: POS Tagging as a Case Study. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-2015), pp. 1783-1792. Beijing, 26-31 July 2015[C] [http://aclweb.org/anthology/P/P15/P15-1172.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> == 2014 ==<br /> *Zhenghua Li, Min Zhang, Wanxiang Che, Ting Liu, Wenliang Chen. 2014. Joint Optimization for Chinese POS Tagging and Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2014. 22(1), pp. 274-286.[J] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-taslp14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Soft Cross-lingual Syntax Projection for Dependency Parsing. Proceedings of the 25th International Conference on Computational Linguistics (COLING-2014), pp. 783-793. Dublin, 23-29 Aug. 2014[C][http://hlt.suda.edu.cn/~zhli/papers/zhenghua-coling14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Ambiguity-aware Ensemble Training for Semi-supervised Dependency Parsing. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL-2014), pp. 457-467. Baltimore, 22-27 June 2014[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl14.pdf PDF] <br /> <br /> * Min ZHANG, Xiangyu Duan, Wenliang CHEN. Bayesian Constituent Context Model for Grammar Induction. IEEE/ACM Transactions on Audio, Speech and Language Processing, 22(2):531-541, 2014[J]<br /> <br /> * Xiangyu Duan, Min Zhang, Qiaoming Zhu. Synchronous Constituent Context Model for Inducing Bilingual Synchronous Structures. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp783-793, Dublin, Ireland, August 2014<br /> <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp816-826, Dublin, Ireland, August 2014<br /> <br /> == 2013 ==<br /> * Min Zhang, Wenliang Chen*, Xiangyu Duan, and Rong Zhang. Improving Graph-based Dependency Parsing Models with Dependency Language Models. IEEE Transactions on Audio, Speech and Language Processing (IEEE-TASL), Vol.21, No.11, pp2313-2323 November 2013. <br /> <br /> * Muhua Zhu, Yue Zhang, Wenliang Chen, Min Zhang, and Jingbo Zhu. Fast and Accurate Constituent Parsing. In Proc. of ACL2013, pp 434-443, Sofia, Bulgaria, August 2013.<br /> <br /> * Xiangyu Duan, Min Zhang, Wenliang Chen. Smoothing for Bracketing Induction. In Proc. of IJCAI2013, pp 2085-2091, Beijing, China, August 2013.<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang. Semi-Supervised Feature Transformation for Dependency Parsing. In Proc. of EMNLP2013, pp1303-1313, Seattle, Washington, USA, 18-21 October 2013.<br /> <br /> == 更古老 ==<br /> <br /> * 请查看各位成员的主页<br /> <br /> <br /> == 参考格式 ==<br /> 期刊格式：[作者列表]. [题目]. [期刊名], [卷号(期):起止页码], [年份][J]<br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> 会议格式：[作者列表]. [题目]. [In Proc. of 会议名], [起止页码], [地点], [会议时间][C] <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING-2014), pp816-826, Dublin, Ireland, August 2014[C]<br /> <br /> 录用格式：[作者列表]. [题目]. [期刊名/会议名], 已录用<br /> * Wenliang Chen. Feature Embedding for Dependency Parsing. CCL-2017, 已录用</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Papers&diff=4876 2022-06-27T07:32:15Z

<p>Xjshi：/* 2021 */</p> <hr /> <div>文章(格式见页尾)包括：<br /> * xACL(ACL/NAACL/EACL/AACL) EMNLP IJCAI AAAI COLING IJCNLP NLPCC<br /> * CCF-A/B Journal/Conference<br /> * SCI Journal<br /> * 软件学报/计算机学报/中国科学<br /> <br /> == [http://hlt.suda.edu.cn/index.php/Papers-details 论文摘要等信息] ==<br /> <br /> == 最新录用 ==<br /> <br /> == 2022 ==<br /> <br /> <br /> * Yahui Liu, Haoping Yang, Chen Gong*, Qingrong Xia, Zhenghua Li, Min Zhang. 2022. MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset. In '''NAACL'''. [http://arxiv.org/abs/2205.06703 arxiv]<br /> * Yue Zhang, Zhenghua Li*, Zuyi Bao, Jiacheng Li, Bo Zhang, Chen Li, Fei Huang, Min Zhang. 2022. MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction. In '''NAACL'''. [https://arxiv.org/abs/2204.10994 arxiv]<br /> * Ying Li, Shuaike Li, Min Zhang. 2022. Semi-supervised Domain Adaptation for Dependency Parsing with Dynamic Matching Network. In '''ACL 2022'', pages 1035--1045. [https://aclanthology.org/2022.acl-long.74.pdf official-pdf] [http://hlt.suda.edu.cn/index.php/%E6%96%87%E4%BB%B6:Liying_ACL2022_camera_ready.pdf camera ready pdf] [https://underline.io/lecture/52551-long-semi-supervised-domain-adaptation-for-dependency-parsing-with-dynamic-matching-network video].<br /> * Houquan Zhou, Yang Li, Zhenghua Li, and Min Zhang. 2022. Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging. In Findings of the Association for Computational Linguistics: ACL 2022, pages 3276–3290, Dublin, Ireland. Association for Computational Linguistics. [http://hlt.suda.edu.cn/LA/papers/acl-findings-hqzhou-bridging.pdf pdf] [https://arxiv.org/pdf/2203.10315 camera ready pdf] [https://aclanthology.org/2022.findings-acl.259.pdf offcial pdf] [https://underline.io/lecture/49965-findings-bridging-pre-trained-language-models-and-hand-crafted-features-for-unsupervised-pos-tagging video]<br /> * Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Yuan, Min Zhang. Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph. IJCAI. 2022<br /> <br /> == 2021 ==<br /> <br /> * Yang Hou, Houquan Zhou, Zhenghua Li*, Yu Zhang, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. A Coarse-to-Fine Labeling Framework for Joint Word Segmentation, POS Tagging, and Constituent Parsing. Proceedings of CoNLL-2021, pp. 290–299. Punta Cana, Dominican Republic (Online), 10-11 Nov. 2021. [[文件:CoNLL_2021_yhou_official_version.pdf]]<br /> <br /> * Kun Wu, Lijie Wang, Zhenghua Li, Ao Zhang, Xinyan Xiao, Hua Wu, Min Zhang, Haifeng Wang. Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-Domain Text-to-SQL Parsing. Proceedings of EMNLP-2021, pp. 8974--8983. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP2021_camera_ready_Data_Augmentation_with_Hierarchical_SQL_to_Question_Generation_forCross_domain_Text_to_SQL_Parsing-09101500.pdf ‎]]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Rui Wang, Min Zhang. Stacked AMR Parsing with Silver Data. Proceedings of EMNLP-2021 Findings, pp. 4729--4738. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_Stacked_AMR_Parsing_with_Silver_Data.pdf]]<br /> <br /> * Ying Li, Meishan Zhang, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. APGN: Adversarial and Parameter Generation Networks for Multi-Source Cross-Domain Dependency Parsing. Proceedings of EMNLP-2021 Findings, pp. 1727–1733. Punta Cana, Dominican Republic (Online), 7-11 Nov. 2021. [[文件:EMNLP_2021_yli_camera_ready.pdf]]<br /> <br /> * Chen Gong, Saihao Huang, Houquan Zhou, Zhenghua Li*, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan. An In-depth Study on Internal Structure of Chinese Words. Proceedings of ACL-2021, pp. 5823–5833. Online, Virtual Event, 1-6 Aug. 2021. [[文件:2021.acl-long.452.pdf]]<br /> <br /> * Qingrong Xia, Bo Zhang, Rui Wang, Zhenghua Li*, Yue Zhang, Fei Huang, Luo Si, Min Zhang. 2021. A Unified Span-Based Approach for Opinion Mining with Syntactic Constituents. Proceedings of NAACL-2021, pp. 1795-1804. Mexico City, Mexico (Online), 6-11 June. 2021. [[文件:2021.naacl-main.144.pdf]]<br /> <br /> Jinpeng Zhang, Baijun Ji, Nini Xiao, Xiangyu Duan*, Min Zhang, Yangbin Shi, Weihua Luo: Combining Static Word Embeddings and Contextual Representations for Bilingual Lexicon Induction, ACL 2021 Findings.<br /> <br /> == 2020 == <br /> <br /> * Zhengqiu HE, Wenliang CHEN, Yuyi WANG, Wei ZHANG, Gaochun WANG, Min ZHANG. Improving Neural Relation Extraction with Positive and Unlabeled Learning. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), pp. 7927-7934. New York, 7-12 Feb. 2020，<br /> <br /> * 杨一帆, 马进, 王海涛, 何正球，陈文亮，张民. 基于简介文本的中文人物关系图谱属性补全与纠错. 中国科学-信息科学. V50(7) : 1003-1018(2020)<br /> <br /> * Junjie Yu, Tong Zhu, Wenliang Chen, Wei Zhang and Min Zhang. Improving Relation Extraction with Relational Paraphrase Sentences. COLING2020, pp. 1687-1698. Online, Dec. 2020[http://hlt.suda.edu.cn/images/9/96/Coling2020-junjie2073_Paper.pdf pdf]<br /> <br /> * Tong Zhu, Haitao Wang, Junjie Yu, Xiabing Zhou, Wenliang Chen, Wei Zhang and Min Zhang. Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction. COLING2020. pp. 6436-6447, Online, Dec. 2020 [https://arxiv.org/pdf/2010.16275.pdf pdf], [https://github.com/Spico197/NYT-H 数据下载@github]<br /> <br /> * Baijun JI, Zhirui ZHANG, Xiangyu DUAN, Min ZHANG, Boxing CHEN and Weihua LUO. Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Xiangyu Duan, Baijun Ji, Hao Jia, Min Tan, Min Zhang, Boxing Chen, Weihua Luo, Yue Zhang: Bilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences. The 58th Annual Meeting of the Association for Computational Linguistics (ACL-2020).<br /> <br /> * Kai SONG, Kun WANG, Heng YU, Yue ZHANG, Zhongqiang HUANG, Weihua LUO, Xiangyu DUAN and Min ZHANG. Alignment-Enhanced Transformer for Constraining NMT with Pre-Specified Translations. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2020), New York, 7-12 Feb. 2020<br /> <br /> * Kai Song, Xiaoqing Zhou, Heng Yu, Zhongqiang Huang, Yue Zhang, Weihua Luo, Xiangyu Duan, Min Zhang: Towards Better Word Alignment in Transformer. IEEE ACM Transaction Audio Speech Language Processing (TASLP), 2020.<br /> <br /> * Huaao Zhang,Shigui Qiu, Xiangyu Duan*,Min Zhang: Token Drop mechanism for Neural Machine Translation. The International Conference on Computational Linguistics (Coling-2020) (short paper).<br /> <br /> * Chen Gong, Zhenghua Li, Qingrong Xia, Wenliang Chen and Min Zhang. Hierarchical LSTM with char-subword-word tree-structure representation for Chinese named entity recognition. Science China Information Science, 2020, 63(10):1-15. [[文件:Hierarchical_LSTM_with_char-subword-word_tree-structure_representation_for_Chinese_named_entity_recognition.pdf]]<br /> <br /> * Ying Li, Zhenghua Li* and Min Zhang. Semi-supervised Domain Adaptation for Dependency Parsing via Improved Contextualized Word Representations. Proceedings of COLING-2020. pp. 3806–3817. Barcelona, Spain (Online), 8-13 Dec. 2020.[https://www.aclweb.org/anthology/2020.coling-main.338.pdf pdf] [[文件:Liying-2020.coling-main.338.pdf]]<br /> <br /> * Qingrong Xia, Rui Wang, Zhenghua Li, Yue Zhang and Min Zhang*. Semantic Role Labeling with Heterogeneous Syntactic Knowledge. Proceedings of COLING-2020. pp. 2979-2990. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/2020.coling-main.266.pdf pdf][[文件:Xiaqingrong-2020.coling-main.266.pdf]]<br /> <br /> * Chen Gong, Zhenghua Li*, Bowei Zou and Min Zhang. Multi-grained Chinese Word Segmentation with Weakly Labeled Data. Proceedings of COLING-2020. pp. 2026–2036. Barcelona, Spain (Online), 8-13 Dec. 2020. [https://www.aclweb.org/anthology/D17-1072.pdf pdf][[文件:Gongchen-2020.coling-main.183.pdf]]<br /> <br /> * Lijie Wang, Ao Zhang, Kun Wu, Ke Sun, Zhenghua Li, Hua Wu*, Min Zhang and Haifeng Wang. DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset. Proceedings of EMNLP-2020. pp. 6923-6935. Online, 16-20 Nov. 2020. [https://www.aclweb.org/anthology/2020.emnlp-main.562.pdf pdf][[文件:2020.emnlp-main.562.pdf]]<br /> <br /> * Houquan Zhou, Yu Zhang, Zhenghua Li, and Min Zhang. Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing? Proceedings of NLPCC-2020, pp. 179--191. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo.pdf pdf]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-ijpmo-official-w-content.pdf pdf-official-w-content]) &lt;font color=&quot;#FF0000&quot;&gt;&lt;b&gt;(best paper!)&lt;/b&gt;&lt;/font&gt; <br /> <br /> * Yu Zhao, Mingyue Zhou, Zhenghua Li, and Min Zhang. Dependency Parsing with Noisy Multi-Annotation Data. Proceedings of NLPCC-2020, pp. 120-131. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. ([http://hlt.suda.edu.cn/images/e/e5/212_Final_Manuscript_%281%29.pdf pdf]）([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official.pdf pdf-official]) ([http://hlt.suda.edu.cn/LA/papers/nlpcc-yzhao-official-w-content.pdf pdf-official-w-content])<br /> <br /> * Yu Zhang, Houquan Zhou, Zhenghua Li. 2020. Fast and Accurate Neural CRF Constituency Parsing. Proceedings of IJCAI-2020, pp. 4046-4053. Yokohama, Japan, 11-17 Jul. 2020. [https://www.ijcai.org/Proceedings/2020/0560.pdf pdf-official] [http://hlt.suda.edu.cn/LA/papers/0560.pdf pdf] [[http://hlt.suda.edu.cn/LA/videos/V5.mp4 video(5 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V10.mp4 video(10 min version)]] [[http://hlt.suda.edu.cn/LA/videos/V15.mp4 video(15 min version)]]<br /> <br /> * Yu Zhang, Zhenghua Li, Min Zhang. 2020. Efficient Second-Order TreeCRF for Neural Dependency Parsing. Proceedings of ACL-2020, pp. 3295-3305. Seattle, America, 5-10 Jul. 2020. ][https://www.aclweb.org/anthology/2020.acl-main.302.pdf pdf-official]] [[http://hlt.suda.edu.cn/LA/papers/2020.acl-main.302.pdf pdf]] [[http://hlt.suda.edu.cn/LA/videos/2020-12-28%2022-21-45.mp4 video]]<br /> <br /> * Bo Zhang, Yue Zhang, Rui Wang, Zhenghua Li, Min Zhang. Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks. Proceedings of ACL-2020, pp. 3249-3258. Seattle, America, 5-10 Jul. 2020. [https://www.aclweb.org/anthology/2020.acl-main.297.pdf pdf] [[文件:Zhangbo-acl2020-ppt-5-24.pdf]]<br /> <br /> == 2019 ==<br /> * Zhengqiu He, Wenliang Chen, Zhenghua Li, Wei Zhang, Hao Shao, Min Zhang. 2019. Syntax-aware Entity Representations for Neural Relation Extraction. Artificial Intelligence Journal.275(2019):602-617, October 2019.[https://doi.org/10.1016/j.artint.2019.07.004 online version]<br /> <br /> * Qingrong Xia, Zhenghua Li*, Min Zhang. A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling, Proceedings of EMNLP-2019, pp5385-5395, HongKong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1541.pdf PDF]<br /> <br /> * Xiangyu Duan, Hongfei Yu, Mingming Yin, Min Zhang, Weihua Luo, Yue Zhang. Contrastive Attention Mechanism for Abstractive Sentence Summarization, Proceeding of EMNLP-2019, pp3035–3044, Hong Kong, China, Nov 3 -7, 2019. [C][https://www.aclweb.org/anthology/D19-1301 PDF]<br /> <br /> * Hongfei Yu, Xiaoqing Zhou, Xiangyu Duan, Min Zhang. Layer-wise De-training and Re-training for Convolutional Sequence to Sequence Machine Translation, Asian and Low-Resource Language Information Processing, Vol. 19, No. 2, Article 26[J][https://dl.acm.org/citation.cfm?id=3358414 PDF]<br /> <br /> * Xiangyu Duan, Mingming Yin, Min Zhang, Boxing Chen, Weihua Luo. Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention, Proceeding of ACL-2019, pp3162–3172, Florence, Italy, Jul 28 - Aug 2, 2019. [C] [https://www.aclweb.org/anthology/P19-1305 PDF]<br /> <br /> * Zhenghua Li, Xue Peng, Min Zhang, Rui Wang, Luo Si. 2019. Semi-supervised Domain Adaptation for Dependency Parsing. Proceedings of ACL-2019, pp. 2386-2395. Florence, Italy, 28 Jul. - 2 Aug. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua_acl19_dp_2.pdf PDF]<br /> <br /> * Kai SONG, Yue ZHANG, Heng YU, Weihua LUO, Kun WANG and Min ZHANG. Code-Switching for Enhancing NMT with Pre-Specified Translation. Proceedings of the 20th Annual Conference of the North American Chapter of the ACL (NAACL-2019), 136–144, Minneapolis, 2-7 June 2019 [C]<br /> <br /> * Meishan Zhang, Zhenghua Li, Guohong Fu, Min Zhang. 2019. Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations. Proceedings of NAACL-2019, pp. 1151-1161. Minneapolis, Minnesota, America, 2-7 Jun. 2019.[http://hlt.suda.edu.cn/~zhli/papers/zhang-naacl-2019.pdf PDF]<br /> <br /> * Ying Li, Zhenghua Li, Min Zhang, Rui Wang, Sheng Li, Luo Si. 2019. Self-attentive Biaffine Dependency Parsing. Proceedings of IJCAI-2019, pp. 5067-5073. Macao, China, 10-16 Aug. 2019 [https://www.ijcai.org/proceedings/2019/0704.pdf PDF]<br /> <br /> * Qingrong Xia, Zhenghua Li, Min Zhang, Meishan Zhang, Guohong Fu, Rui Wang, Luo Si. 2019. Syntax-aware Neural Semantic Role Labeling. Proceedings of AAAI-2019, pp. x-x. Honolulu, Hawaii, America, 27 Jan. - 1 Feb. 2019. [http://hlt.suda.edu.cn/kiro/papers/aaai19.pdf PDF]<br /> <br /> * 周俊佐, 朱宗奎, 何正球, 陈文亮, 张民. 面向人机对话意图分类的混合神经网络模型. 软件学报. 2019,30(11):3313-3325[http://www.jos.org.cn/jos/ch/reader/view_abstract.aspx?file_no=5862&amp;flag=1 PDF]<br /> <br /> == 2018 ==<br /> <br /> * Xinzhou Jiang, Bo Zhang, Zhenghua Li, Min Zhang, Sheng Li, Luo Si. Supervised Treebank Conversion: Data and Approaches. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL-2018), pp. 2706-2716. Melbourne, Australia. 15-20 Jul. 2018[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl18.pdf PDF]<br /> <br /> * Yachao Li, Junhui Li, Min Zhang. Adapted Weights for Neural Machine Translation. In Proceedings of COLING-2018, pp. 3038–3048, Santa Fe, New Mexico, USA, August 20-26, 2018[C]<br /> <br /> * Yaosheng Yang, Wenliang Chen, Zhenghua Li, Zhengqiu He and Min Zhang. Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning, Proceedings of COLING2018, pp.2159–2169, Santa Fe, New Mexico, USA, August 20-26, 2018[C] [https://github.com/rainarch/DSNER Code] [http://aclweb.org/anthology/C18-1183 PDF]<br /> <br /> * Kai Song, Yue Zhang, Min Zhang, Weihua Luo. Improved English to Russian Translation by Neural Suffix Prediction, Proceedings of AAAI-2018, pp410-417, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03615 PDF]<br /> <br /> * YaoSheng Yang, Meishan Zhang, Wenliang Chen*, Haofen Wang, Wei Zhang, Min Zhang. Adversarial Learning for Chinese NER from Crowd Annotations, Proceedings of AAAI-2018, pp1627-1634, New Orleans, USA,Feb 2018[C] [https://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Zhengqiu He, Wenliang Chen*, Zhenghua Li, Meishan Zhang, Wei Zhang, Min Zhang. SEE: Syntax-aware Entity Embedding for Neural Relation Extraction, Proceedings of AAAI-2018, pp5795-5802, New Orleans, USA,Feb 2018[C] [http://arxiv.org/abs/1801.03603 PDF]<br /> <br /> * Qi Lu, YaoSheng Yang, Zhenghua Li, Wenliang Chen and Min Zhang. M-CNER: A Corpus for Chinese Named Entity Recognition in Multi-Domains, Proceedings of LREC-2018, pp4458-4461, Japan, May 2018 [http://hlt.suda.edu.cn/~zhli/papers/lrec-2018-ner.pdf PDF]<br /> <br /> == 2017 ==<br /> * Wenliang Chen, Muhua Zhu, Min Zhang, Yue Zhang, Jingbo Zhu. Improving Shift-Reduce Phrase-Structure Parsing with Constituent Boundary Information. Computational Intelligence Journal, 33(3):428-447, August 2017[J]<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen, Meishan Zhang, Guohong Fu. 2016. Coupled POS Tagging on Heterogeneous Annotations. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2017. 25(3), pp. 557-571.[http://hlt.suda.edu.cn/~zhli/papers/zhenghua-ieee17-coupled-pos.pdf PDF]<br /> <br /> * Yue Zhang, Zhenghua Li, Jun Lang, Qingrong Xia, Min Zhang. 2017. Dependency Parsing with Partial Annotations: An Empirical Comparison. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-2017), pp. 49-58. Taiwan, Nov. 27 - Dec. 1, 2017[C] [http://aclweb.org/anthology/I/I17/I17-1006.pdf PDF]<br /> <br /> * Chen Gong, Zhenghua Li, Min Zhang, Xinzhou Jiang. 2017. Multi-Grained Chinese Word Segmentation. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP-2017), pp. 703-714. Copenhagen, Denmark, 7-11 Sept. 2017[C] [http://hlt.suda.edu.cn/~zhli/papers/chen-d17-mws.pdf PDF]<br /> <br /> == 2016 ==<br /> <br /> * Zhenghua Li, Jiayuan Chao, Min Zhang, Jiwen Yang. Fast Coupled Sequence Labeling on Heterogeneous Annotations via Context-aware Pruning. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-2016), pp. 753-762. Austin, Texas, USA, 1-5 Nov. 2016[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-emnlp-2016-submission.pdf PDF]<br /> <br /> * Zhenghua Li, Min Zhang, Yue Zhang, Zhanyi Liu, Wenliang Chen, Hua Wu, Haifeng Wang. Active Learning for Dependency Parsing with Partial Annotation. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-2016), pp. 344-354. Berlin, 7-12 Aug. 2016[C] [http://hlt.suda.edu.cn/~zhli/acl-2016-resources/zhenghua-acl2016-camera-ready.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang, Xiangyu Duan. Exploiting Meta Features for Dependency Parsing and Part-of-speech Tagging. Artificial Intelligence Journal, 230(2016):173-191, January 2016[J]<br /> <br /> * Wenliang Chen, Zhenjie Zhang, Zhenghua Li, Min Zhang. Distributed Representations for Building Profiles of Users and Items from Text Reviews. In Proc. of the 26th International Conference on Computational Linguistics (COLING-2016), pp2143-2153, Osaka, 11-17 Dec. 2016[C][https://www.aclweb.org/anthology/C16-1202.pdf PDF]<br /> <br /> == 2015 ==<br /> *Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Chen. 2015. Coupled Sequence Labeling on Heterogeneous Annotations: POS Tagging as a Case Study. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-2015), pp. 1783-1792. Beijing, 26-31 July 2015[C] [http://aclweb.org/anthology/P/P15/P15-1172.pdf PDF]<br /> <br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> == 2014 ==<br /> *Zhenghua Li, Min Zhang, Wanxiang Che, Ting Liu, Wenliang Chen. 2014. Joint Optimization for Chinese POS Tagging and Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM-TASL [J]). 2014. 22(1), pp. 274-286.[J] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-taslp14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Soft Cross-lingual Syntax Projection for Dependency Parsing. Proceedings of the 25th International Conference on Computational Linguistics (COLING-2014), pp. 783-793. Dublin, 23-29 Aug. 2014[C][http://hlt.suda.edu.cn/~zhli/papers/zhenghua-coling14.pdf PDF]<br /> <br /> *Zhenghua Li, Min Zhang, Wenliang Chen. 2014. Ambiguity-aware Ensemble Training for Semi-supervised Dependency Parsing. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL-2014), pp. 457-467. Baltimore, 22-27 June 2014[C] [http://hlt.suda.edu.cn/~zhli/papers/zhenghua-acl14.pdf PDF] <br /> <br /> * Min ZHANG, Xiangyu Duan, Wenliang CHEN. Bayesian Constituent Context Model for Grammar Induction. IEEE/ACM Transactions on Audio, Speech and Language Processing, 22(2):531-541, 2014[J]<br /> <br /> * Xiangyu Duan, Min Zhang, Qiaoming Zhu. Synchronous Constituent Context Model for Inducing Bilingual Synchronous Structures. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp783-793, Dublin, Ireland, August 2014<br /> <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING2014), pp816-826, Dublin, Ireland, August 2014<br /> <br /> == 2013 ==<br /> * Min Zhang, Wenliang Chen*, Xiangyu Duan, and Rong Zhang. Improving Graph-based Dependency Parsing Models with Dependency Language Models. IEEE Transactions on Audio, Speech and Language Processing (IEEE-TASL), Vol.21, No.11, pp2313-2323 November 2013. <br /> <br /> * Muhua Zhu, Yue Zhang, Wenliang Chen, Min Zhang, and Jingbo Zhu. Fast and Accurate Constituent Parsing. In Proc. of ACL2013, pp 434-443, Sofia, Bulgaria, August 2013.<br /> <br /> * Xiangyu Duan, Min Zhang, Wenliang Chen. Smoothing for Bracketing Induction. In Proc. of IJCAI2013, pp 2085-2091, Beijing, China, August 2013.<br /> <br /> * Wenliang Chen, Min Zhang, Yue Zhang. Semi-Supervised Feature Transformation for Dependency Parsing. In Proc. of EMNLP2013, pp1303-1313, Seattle, Washington, USA, 18-21 October 2013.<br /> <br /> == 更古老 ==<br /> <br /> * 请查看各位成员的主页<br /> <br /> <br /> == 参考格式 ==<br /> 期刊格式：[作者列表]. [题目]. [期刊名], [卷号(期):起止页码], [年份][J]<br /> * Wenliang Chen, Min Zhang*, Yue Zhang. Distributed Feature Representations for Dependency Parsing. IEEE/ACM Transactions on Audio, Speech and Language Processing, 23(3):451-460, 2015[J]<br /> <br /> 会议格式：[作者列表]. [题目]. [In Proc. of 会议名], [起止页码], [地点], [会议时间][C] <br /> * Wenliang Chen, Yue Zhang, Min Zhang*. Feature Embedding for Dependency Parsing. In Proc. of the 25th International Conference on Computational Linguistics (COLING-2014), pp816-826, Dublin, Ireland, August 2014[C]<br /> <br /> 录用格式：[作者列表]. [题目]. [期刊名/会议名], 已录用<br /> * Wenliang Chen. Feature Embedding for Dependency Parsing. CCL-2017, 已录用</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Members&diff=4659 2022-04-16T05:08:18Z

<p>Xjshi：</p> <hr /> <div><br /> == 在校老师 ==<br /> * [[Faculty|English Version]]<br /> * 教师：[https://zhangminsuda.github.io/ 张民]、付国宏、[[Wenliang|陈文亮]]、[http://hlt.suda.edu.cn/index.php/%E6%AE%B5%E6%B9%98%E7%85%9C 段湘煜]、[http://hlt.suda.edu.cn/~zhli/ 李正华]、[http://web.suda.edu.cn/zhouxiabing/ 周夏冰]、[http://web.suda.edu.cn/cm/ 曹敏]、[https://lijuntaopku.github.io/ 李俊涛]、冯思为、曹自强<br /> * 科研助理：[[仇慧敏]]<br /> <br /> == 在校学生（[http://hlt.suda.edu.cn/index.php/Stu_candidates 招生说明]）==<br /> <br /> * 2016博：李亚超（1） <br /> <br /> * 2017博：[[郁俊杰]]、[[宋楷]] (2)<br /> <br /> * 2019博：贾昊、余南 (2)<br /> <br /> * 2020博：刘振华、梁晓波、张建新 (3)<br /> <br /> * 2021博：朱桐、周厚全、张宇<br /> <br /> * 2019硕：贾永辉、[https://spico197.github.io/ 朱桐]、沈嘉钰、杨浩苹、周厚全、周明月、贾浩、章华奥、王煦、吴世龙、邱石贵、张世奇、陈楠、陈晨、李子仪（15）<br /> <br /> * 2020硕：张智林、张国梁、陈跃鹤、张飞宇、周沛、侯洋、李帅克、周仕林、李嘉诚、李扬、刘泽洋、张金鹏、金畅、肖妮妮、段仁翀<br /> <br /> * 2021硕：谈川源、任俊飞、余子健、项健翔、刘资蕴、章岳、黄赛豪、窦晨晖、严福康、崔秀莲、张磊、周烁、张竹君、董川奇、周文杰、缪思睿<br /> <br /> == 访问学者/学生==<br /> * 访问学者：秦彦霞（东华大学讲师，哈工大博士）<br /> * 访问学生：杨明明（哈工大博士生）<br /> <br /> == 毕业学生(毕业第一次工作去向) ==<br /> <br /> === 博士 ===<br /> <br /> * 2022毕业博：[http://hlt.suda.edu.cn/gongchen/ 龚晨]、[http://hlt.suda.edu.cn/kiro 夏庆荣]、[[李英]]、<br /> <br /> * 2018毕业博：王星（腾讯AILab）<br /> <br /> === 硕士 ===<br /> * 2021毕业硕：方晔玮（百度）、王海涛（华为）、马进（美团）、张鹏举（腾讯）、王铭涛（苏大）、蒋炜、刘亚慧、陆凯华、吴锟、张宇、季佰军（腾讯）、史小静（搜狗）、宁秋怡（联通）、肖康（14）<br /> <br /> * 2020毕业硕：张栋（同花顺）、杨一帆（思必驰）、朱宗奎（华为）、周俊佐（阿里巴巴）、郁圣卫、黄德朋、[http://hlt.suda.edu.cn/LA/xzjiang/ 江心舟]、彭雪、[http://hlt.suda.edu.cn/bozhang/ 章波]、谭敏（华为）、周孝青（OPPO）、殷明明（搜狗）、俞鸿飞（美团） (13)<br /> <br /> * 2019毕业硕：何正球（美团）、杨耀晟（阿里巴巴）、郭丽娟（狗尾草）、孙佳伟（苏州微软）、朱运（搜狗）、汪琪（深圳招商银行总行）、王坤（杭州搜狗研究院）、龚晨（苏大读博）、夏庆荣（苏大读博） (9)<br /> <br /> * 2018毕业硕：陈伟（爱奇艺）、凡子威（搜狗）、卢奇（美团）、张月（阿里巴巴） (4)<br /> <br /> * 2017毕业硕：巢佳媛（阿里巴巴公司）、陈志鹏（百度公司）、龚慧敏（同程公司）、郁俊杰（苏大读博）(4)<br /> <br /> * 2016毕业硕：马春平（阿里巴巴公司）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Members&diff=4658 2022-04-16T04:56:48Z

<p>Xjshi：</p> <hr /> <div><br /> == 在校老师 ==<br /> * [[Faculty|English Version]]<br /> * 教师：[https://zhangminsuda.github.io/ 张民]、付国宏、[[Wenliang|陈文亮]]、[http://hlt.suda.edu.cn/index.php/%E6%AE%B5%E6%B9%98%E7%85%9C 段湘煜]、[http://hlt.suda.edu.cn/~zhli/ 李正华]、[http://web.suda.edu.cn/zhouxiabing/ 周夏冰]、[http://web.suda.edu.cn/cm/ 曹敏]、[https://lijuntaopku.github.io/ 李俊涛]、冯思为、曹自强<br /> * 科研助理：[[仇慧敏]]<br /> <br /> == 在校学生（[http://hlt.suda.edu.cn/index.php/Stu_candidates 招生说明]）==<br /> <br /> * 2016博：李亚超（1） <br /> <br /> * 2017博：[[郁俊杰]]、[[宋楷]] (2)<br /> <br /> * 2019博：贾昊、余南 (2)<br /> <br /> * 2020博：刘振华、梁晓波、张建新 (3)<br /> <br /> * 2021博：朱桐、周厚全、张宇<br /> <br /> * 2019硕：贾永辉、[https://spico197.github.io/ 朱桐]、沈嘉钰、杨浩苹、周厚全、周明月、贾浩、章华奥、王煦、吴世龙、邱石贵、张世奇、陈楠、陈晨、李子仪（15）<br /> <br /> * 2020硕：张智林、张国梁、陈跃鹤、张飞宇、周沛、侯洋、李帅克、周仕林、李嘉诚、李扬、刘泽洋、张金鹏、金畅、肖妮妮、段仁翀<br /> <br /> * 2021硕：谈川源、任俊飞、余子健、项健翔、刘资蕴、章岳、黄赛豪、窦晨晖、严福康、崔秀莲、张磊、周烁、张竹君、董川奇、周文杰、缪思睿<br /> <br /> == 访问学者/学生==<br /> * 访问学者：秦彦霞（东华大学讲师，哈工大博士）<br /> * 访问学生：杨明明（哈工大博士生）<br /> <br /> == 毕业学生(毕业第一次工作去向) ==<br /> <br /> === 博士 ===<br /> <br /> * 2022毕业博：[http://hlt.suda.edu.cn/gongchen/ 龚晨]、[http://hlt.suda.edu.cn/kiro 夏庆荣]、[[李英]]、<br /> <br /> * 2018毕业博：王星（腾讯AILab）<br /> <br /> === 硕士 ===<br /> * 2021毕业硕：方晔玮（百度）、王海涛（华为）、马进（美团）、张鹏举（腾讯）、王铭涛（苏大）、蒋炜、刘亚慧、陆凯华、吴锟、张宇、季佰军、史小静、宁秋怡、肖康（14）<br /> <br /> * 2020毕业硕：张栋（同花顺）、杨一帆（思必驰）、朱宗奎（华为）、周俊佐（阿里巴巴）、郁圣卫、黄德朋、[http://hlt.suda.edu.cn/LA/xzjiang/ 江心舟]、彭雪、[http://hlt.suda.edu.cn/bozhang/ 章波]、谭敏、周孝青、殷明明、俞鸿飞 (13)<br /> <br /> * 2019毕业硕：何正球（美团）、杨耀晟（阿里巴巴）、郭丽娟（狗尾草）、孙佳伟（苏州微软）、朱运（搜狗）、汪琪（深圳招商银行总行）、王坤（杭州搜狗研究院）、龚晨（苏大读博）、夏庆荣（苏大读博） (9)<br /> <br /> * 2018毕业硕：陈伟（爱奇艺）、凡子威（搜狗）、卢奇（美团）、张月（阿里巴巴） (4)<br /> <br /> * 2017毕业硕：巢佳媛（阿里巴巴公司）、陈志鹏（百度公司）、龚慧敏（同程公司）、郁俊杰（苏大读博）(4)<br /> <br /> * 2016毕业硕：马春平（阿里巴巴公司）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4587 2022-03-28T01:54:21Z

<p>Xjshi：撤销Xjshi（讨论）的版本3281</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://hlt.suda.edu.cn/~xyduan/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4586 2022-03-28T01:52:42Z

<p>Xjshi：撤销Xjshi（讨论）的版本3398</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被[https://www.aclweb.org/anthology/2020.findings-emnlp.377.pdf EMNLP2020-Findings]接收。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被[https://www.aclweb.org/anthology/2020.coling-main.379.pdf COLING2020接收](短文)。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4585 2022-03-28T01:51:23Z

<p>Xjshi：撤销Xjshi（讨论）的版本4584</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家重点研发计划“政府间国际科技创新合作”重点专项一项，国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被[https://www.aclweb.org/anthology/2020.findings-emnlp.377.pdf EMNLP2020-Findings]接收。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被[https://www.aclweb.org/anthology/2020.coling-main.379.pdf COLING2020接收](短文)。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4584 2022-03-26T01:00:03Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院，教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647 <br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> <br /> '''简介'''<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> <br /> '''研究领域'''<br /> <br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> <br /> '''最近更新'''<br /> <br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings]接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://aclanthology.org/2020.acl-main.143.pdf ACL2020]接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020]接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP]接收，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020]接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被[https://aclanthology.org/2020.findings-emnlp.377.pdf EMNLP2020-Findings]接收。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> -----------------------------------------<br /> <br /> '''学生'''<br /> <br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> <br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于京东，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> [http://hlt.suda.edu.cn/translation/#/translation '''中英翻译演示系统''']</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4455 2022-01-30T07:09:26Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家重点研发计划“政府间国际科技创新合作”重点专项一项，国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被[https://www.aclweb.org/anthology/2020.findings-emnlp.377.pdf EMNLP2020-Findings]接收。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被[https://www.aclweb.org/anthology/2020.coling-main.379.pdf COLING2020接收](短文)。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation, 现就职于腾讯，北京<br /> <br /> 宁秋怡, Domain-adapted Machine Translation, 现就职于联通，南京<br /> <br /> 史小静, Domain-adapted Machine Translation, 现就职于搜狗，杭州<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4338 2021-12-22T07:04:45Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院，教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647<br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> <br /> '''简介'''<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> <br /> '''研究领域'''<br /> <br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> <br /> '''最近更新'''<br /> <br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings]接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://aclanthology.org/2020.acl-main.143.pdf ACL2020]接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020]接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP]接收，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020]接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被[https://aclanthology.org/2020.findings-emnlp.377.pdf EMNLP2020-Findings]接收。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> -----------------------------------------<br /> <br /> '''学生'''<br /> <br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> <br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于京东，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> [http://hlt.suda.edu.cn/translation/#/translation '''中英翻译演示系统''']</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4241 2021-10-12T04:09:39Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647<br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> <br /> '''简介'''<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> <br /> '''研究领域'''<br /> <br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> <br /> '''最近更新'''<br /> <br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings]接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://aclanthology.org/2020.acl-main.143.pdf ACL2020]接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020]接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP]接收，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020]接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被[https://aclanthology.org/2020.findings-emnlp.377.pdf EMNLP2020-Findings]接收。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> -----------------------------------------<br /> <br /> '''学生'''<br /> <br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> <br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于京东，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> [http://hlt.suda.edu.cn/translation/#/translation '''中英翻译演示系统''']</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4240 2021-10-12T04:05:27Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647<br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> <br /> '''简介'''<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> <br /> '''研究领域'''<br /> <br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> <br /> '''最近更新'''<br /> <br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings]接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://aclanthology.org/2020.acl-main.143.pdf ACL2020]接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020]接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP]接收，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020]接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被[https://aclanthology.org/2020.findings-emnlp.377.pdf EMNLP2020-Findings]接收。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> -----------------------------------------<br /> <br /> '''学生'''<br /> <br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> <br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于京东，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> [http://hlt.suda.edu.cn/translation/#/translation 中英翻译演示系统]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4239 2021-10-12T04:03:30Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647<br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> <br /> '''简介'''<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> <br /> '''研究领域'''<br /> <br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> <br /> '''最近更新'''<br /> <br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings]接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://aclanthology.org/2020.acl-main.143.pdf ACL2020]接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020]接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP]接收，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418v AAAI2020]接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被[https://aclanthology.org/2020.findings-emnlp.377.pdf EMNLP2020-Findings]接收。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> -----------------------------------------<br /> <br /> '''学生'''<br /> <br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> <br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于京东，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> [http://hlt.suda.edu.cn/translation/#/translation 中英翻译演示系统]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4238 2021-10-12T03:59:02Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647<br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> <br /> '''简介'''<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> <br /> '''研究领域'''<br /> <br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> <br /> '''最近更新'''<br /> <br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被ACL2021-Findings接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被ACL2020接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被AAAI2020接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被TASLP接收，以及AAAI2020接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被EMNLP2020-Findings接收。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> -----------------------------------------<br /> <br /> '''学生'''<br /> <br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> <br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> [http://hlt.suda.edu.cn/translation/#/translation 中英翻译演示系统]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4237 2021-10-12T03:57:15Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647<br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> '''简介'''<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> 研究领域<br /> <br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> 最近更新<br /> <br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被ACL2021-Findings接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被ACL2020接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被AAAI2020接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被TASLP接收，以及AAAI2020接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被EMNLP2020-Findings接收。<br /> <br /> 更多信息请参看个人主页。<br /> <br /> -----------------------------------------<br /> 学生<br /> <br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> [http://hlt.suda.edu.cn/translation/#/translation 中英翻译演示系统]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4236 2021-10-12T03:53:52Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647<br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> 简介<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> 研究领域<br /> <br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> 最近更新<br /> <br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被ACL2021-Findings接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被ACL2020接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被AAAI2020接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被TASLP接收，以及AAAI2020接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被EMNLP2020-Findings接收。<br /> <br /> 更多信息请参看个人主页。<br /> <br /> -----------------------------------------<br /> 学生<br /> <br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> [http://hlt.suda.edu.cn/translation/#/translation 中英翻译演示系统]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4235 2021-10-12T03:51:47Z

<p>Xjshi：</p> <hr /> <div>[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647<br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> 简介<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> 研究领域<br /> <br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> 最近更新<br /> <br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被ACL2021-Findings接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被ACL2020接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被AAAI2020接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被TASLP接收，以及AAAI2020接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被EMNLP2020-Findings接收。<br /> <br /> 更多信息请参看个人主页。<br /> <br /> -----------------------------------------<br /> 学生<br /> <br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> [http://hlt.suda.edu.cn/translation/#/translation 中英翻译演示系统]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4234 2021-10-12T03:50:27Z

<p>Xjshi：</p> <hr /> <div>[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647<br /> <br /> 地址：苏州大学理工楼435，email: xiangyuduan@suda.edu.cn<br /> <br /> <br /> -----------------------------------------<br /> 简介<br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，国家重点研发计划“政府间国际科技创新合作”重点专项一项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> -----------------------------------------<br /> 研究领域<br /> 机器翻译<br /> <br /> 跨语言信息处理<br /> <br /> 自然语言处理基本模块，词法、句法分析等<br /> <br /> -----------------------------------------<br /> 最近更新<br /> 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被ACL2021-Findings接收。<br /> <br /> 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被ACL2020接收。<br /> <br /> 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被AAAI2020接收。<br /> <br /> 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被TASLP接收，以及AAAI2020接收。<br /> <br /> 建模领域共有特征和各领域特有特征，我们提出了多领域适应的Transformer模型，该工作被EMNLP2020-Findings接收。<br /> <br /> 更多信息请参看个人主页。<br /> <br /> -----------------------------------------<br /> 学生<br /> 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> <br /> <br /> 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> 史小静, Domain-adapted Machine Translation，现就职于搜狗，杭州<br /> <br /> 宁秋怡，Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> -----------------------------------------<br /> <br /> 中英翻译演示系统</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4233 2021-10-12T03:47:14Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4232 2021-10-12T03:43:37Z

<p>Xjshi：</p> <hr /> <div>[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群:984586647</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4231 2021-10-12T03:42:14Z

<p>Xjshi：</p> <hr /> <div>[https://xyda.github.io/ 请参见个人主页]，学生信息可参考学生QQ群: 984586647</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4230 2021-10-12T03:40:18Z

<p>Xjshi：</p> <hr /> <div>[http://hlt.suda.edu.cn/index.php/段湘煜 请参见个人主页]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4229 2021-10-12T03:39:26Z

<p>Xjshi：页面内容被替换为“[http://hlt.suda.edu.cn/index.php/%E6%AE%B5%E6%B9%98%E7%85%9C 请参见个人主页]”</p> <hr /> <div>[http://hlt.suda.edu.cn/index.php/%E6%AE%B5%E6%B9%98%E7%85%9C 请参见个人主页]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4224 2021-09-23T00:57:40Z

<p>Xjshi：/* 最近更新 */</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings接收]。<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[https://xyda.github.io/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> <br /> 史小静, Domain-adapted Machine Translation，先就职于搜狗，杭州<br /> <br /> 宁秋怡, Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> == 中英翻译演示系统 ==<br /> <br /> http://hlt.suda.edu.cn/translation/#/translation （受限内网管制，每晚6点后不能访问）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4223 2021-09-23T00:56:59Z

<p>Xjshi：/* 最近更新 */</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 结合静态词嵌入和动态上下文嵌入，我们提出了新的翻译词对发现方法，该工作被[https://aclanthology.org/2021.findings-acl.260.pdf ACL2021-Findings接收]。<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> <br /> 史小静, Domain-adapted Machine Translation，先就职于搜狗，杭州<br /> <br /> 宁秋怡, Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> == 中英翻译演示系统 ==<br /> <br /> http://hlt.suda.edu.cn/translation/#/translation （受限内网管制，每晚6点后不能访问）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=4042 2021-07-06T08:08:55Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 季佰军, Zero-shot Machine Translation，现就职于腾讯，北京<br /> <br /> 史小静, Domain-adapted Machine Translation，先就职于搜狗，杭州<br /> <br /> 宁秋怡, Domain-adapted Machine Translation，现就职于联通，南京<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于微软，苏州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> == 中英翻译演示系统 ==<br /> <br /> http://hlt.suda.edu.cn/translation/#/translation （受限内网管制，每晚6点后不能访问）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=3742 2021-04-01T01:29:54Z

<p>Xjshi：/* 中英翻译演示系统 */</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 季佰军, Zero-shot Machine Translation<br /> <br /> 宁秋怡, Domain-adapted Machine Translation<br /> <br /> 史小静, Domain-adapted Machine Translation<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> == 中英翻译演示系统 ==<br /> <br /> http://hlt.suda.edu.cn/translation/#/translation （受限内网管制，每晚6点后不能访问）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=3720 2021-03-24T02:43:02Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[https://xyda.github.io/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 季佰军, Zero-shot Machine Translation<br /> <br /> 宁秋怡, Domain-adapted Machine Translation<br /> <br /> 史小静, Domain-adapted Machine Translation<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> == 中英翻译演示系统 ==<br /> <br /> http://hlt.suda.edu.cn/translation/#/translation （受限内网管制，每晚8点后不能访问）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Research_groups&diff=3717 2021-03-23T09:32:33Z

<p>Xjshi：/* MT （机器翻译组） */</p> <hr /> <div>== LA（语言分析组） ==<br /> <br /> 负责老师：[http://hlt.suda.edu.cn/~zhli 李正华]<br /> <br /> 具体课题：<br /> <br /> * 分词（多粒度分词）：数据标注、模型和算法<br /> * 词性标注：模型和算法<br /> * 依存句法分析：标注规范、数据标注、模型和算法<br /> * 语义分析（各种语义表示如SDP、DM、UCCA、EDS、AMR等、语义知识挖掘如上下位关系）：模型和算法<br /> * 演示系统：[http://hlt-la.suda.edu.cn 苏州大学语言理解平台（CUP）]，苏州大学数据标注平台（DAP）等，请看我的主页。<br /> <br /> == KG/QA （知识图谱/问答组）==<br /> 负责老师：陈文亮<br /> <br /> 具体课题：<br /> * 实体识别：多语言、多领域NER数据和模型<br /> * 关系抽取：基于机器学习的抽取模型、基于模板的抽取模型<br /> * 实体情感分析<br /> * 知识图谱数据融合<br /> * KBQA，对话系统<br /> <br /> == MT （机器翻译组）==<br /> 负责老师：[http://hlt.suda.edu.cn/index.php/%E6%AE%B5%E6%B9%98%E7%85%9C 段湘煜]<br /> <br /> 具体课题：<br /> * [http://hlt.suda.edu.cn/translation/#/translation 神经机器翻译]</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=3716 2021-03-23T09:08:42Z

<p>Xjshi：/* 中英翻译演示系统 */</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://hlt.suda.edu.cn/~xyduan/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 季佰军, Zero-shot Machine Translation<br /> <br /> 宁秋怡, Domain-adapted Machine Translation<br /> <br /> 史小静, Domain-adapted Machine Translation<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> == 中英翻译演示系统 ==<br /> <br /> http://hlt.suda.edu.cn/translation/#/translation （受限内网管制，每晚8点后不能访问）</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=%E6%AE%B5%E6%B9%98%E7%85%9C&diff=3715 2021-03-23T09:06:34Z

<p>Xjshi：</p> <hr /> <div>苏州大学计算机科学与技术学院教授，[http://hlt.suda.edu.cn/~xyduan/ 请参见个人主页], 学生信息可参考学生QQ群: 984586647<br /> <br /> 联系方式：xiangyuduan at suda dot edu dot cn<br /> <br /> Professor, School of Computer Science and Technology, Soochow University. Please visit the [https://sites.google.com/view/xyduan/%E9%A6%96%E9%A1%B5 homepage]<br /> <br /> Contact: xiangyuduan at suda dot edu dot cn<br /> <br /> <br /> == 个人简介 ==<br /> <br /> 2008年1月博士毕业于中国科学院自动化研究所，其后在新加坡科技发展局资讯通信研究院（I2R）任研究员，于2013年加入苏州大学计算机科学与技术学院，2014年获苏州市紧缺人才资助。主要从事自然语言处理方向的研究，包括机器翻译，机器学习等。先后主持国家自然科学基金项目两项，苏州市资助基金项目一项，并曾作为主要研究人员参与中国-新加坡联合项目，国家自然科学基金项目，北京市自然科学基金项目，以及中国和新加坡的若干工业项目。作为负责人在国际口语机器翻译评测任务中多次在众多国际参与单位中取得前三名；作为指导老师，指导研究生获得2018年全球AI挑战赛（AI Challenger）机器翻译赛道双周赛第一名。发表包括IEEE/ACM期刊TASLP，ACL、AAAI、IJCAI、EMNLP、COLING等顶级会议的论文二十余篇，曾担任中国科学-信息科学、软件学报、IEEE/ACM TASLP、ACM TALIP等杂志特邀审稿人以及国际顶级学术会议执委会成员或审稿人。<br /> <br /> == 研究领域 ==<br /> <br /> * 机器翻译<br /> * 跨语言信息处理<br /> * 自然语言处理基本模块，词法、句法分析等<br /> <br /> == 最近更新 ==<br /> <br /> * 模仿人类强大单语语言能力，只需要双语词典就可学习翻译，我们提出了基于双语词典但不需平行语料的机器翻译方法，被[https://www.aclweb.org/anthology/2020.acl-main.143.pdf ACL2020接收]。<br /> <br /> * 基于跨语言预训练，将多语言空间拉近，从而将资源丰富语向的翻译模型直接迁移到零资源的翻译语向上，该工作被[https://ojs.aaai.org//index.php/AAAI/article/view/5341 AAAI2020接收]。<br /> <br /> * 面向可定制的翻译服务，分别提出提升词对齐的方法以及更好地约束输出为定制好的翻译结果的方法，分别被[https://ieeexplore.ieee.org/document/9103090 TASLP接收]，以及[https://ojs.aaai.org//index.php/AAAI/article/view/6418 AAAI2020接收]。<br /> <br /> * 提出符号丢弃(TokenDropout)取代词丢弃(WordDropout)，并应用于神经机器翻译，该工作被COLING2020接收(短文)。<br /> <br /> 更多信息请参看[http://hlt.suda.edu.cn/~xyduan/ 个人主页]。<br /> <br /> == 学生 ==<br /> <br /> * 在读研究生<br /> <br /> 季佰军, Zero-shot Machine Translation<br /> <br /> 宁秋怡, Domain-adapted Machine Translation<br /> <br /> 史小静, Domain-adapted Machine Translation<br /> <br /> 贾浩, Machine Translation, Cross-lingual Applications<br /> <br /> 王煦, Cross-lingual Applications<br /> <br /> 邱石贵, Cross-lingual Applications<br /> <br /> 章华奥, Machine Translation Applications<br /> <br /> 吴世龙, Language Resources<br /> <br /> 张金鹏，Bilingual Lexicon Induction<br /> <br /> 段仁翀，Multilingual Machine Translation<br /> <br /> 金畅，Machine Translation<br /> <br /> 肖妮妮，Machine Translation<br /> <br /> * 已毕业研究生<br /> <br /> 殷明明, cross-lingual summarization, 现就职于搜狗，杭州<br /> <br /> 周孝青, model compression for machine translation, 现就职于OPPO，北京<br /> <br /> 俞鸿飞, machine translation and summarization, 现就职于美团，上海<br /> <br /> 谭敏, machine translation, 现就职于华为，南京<br /> <br /> 王坤, machine translation systems, 现就职于搜狗，杭州<br /> <br /> 汪琪, convolution on attention heatmap of NMT, 现就职于中国招商银行总行，深圳<br /> <br /> 龚慧敏, corpus quality, 现就职于智慧芽，苏州<br /> <br /> == 中英翻译演示系统 ==<br /> <br /> http://hlt.suda.edu.cn/translation/#/translation</div>

Xjshi http://hlt.suda.edu.cn/index.php?title=Demo&diff=3670 2021-03-16T10:38:36Z

<p>Xjshi：</p> <hr /> <div>== LA（语言分析） ==<br /> * [http://hlt-la.suda.edu.cn 汉语理解平台（CUP）]<br /> * [http://139.224.234.18/anno-sys 数据标注平台（DAP）]<br /> * [多粒度分词]<br /> * [英语UCCA语义分析]<br /> <br /> &lt;font xxx&gt; 如果您发现上述链接打不开，请联系李正华 zhli13@suda.edu.cn &lt;/font&gt;<br /> <br /> == KG ==<br /> * [[pBridge | 人物知识图谱在线系统]]<br /> <br /> == MT ==<br /> * [http://hlt.suda.edu.cn/translation/#/translation 机器翻译系统平台 ]</div>

Xjshi