“LA-paper-report-talk-etc”的版本间的差异
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| 第14行： | 第14行： | ||
=== Conference Papers in Chinese === | === Conference Papers in Chinese === | ||
=== Journal Papers In English=== | === Journal Papers In English=== | ||
| − | Chen Gong, Zhenghua Li, Qingrong Xia, Wenliang Chen and Min Zhang. Hierarchical LSTM with char-subword-word tree-structure representation | + | * 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, 63(10):2020. [[文件:Hierarchical LSTM with char-subword-word tree-structure representation for Chinese named entity recognition.pdf]] | for Chinese named entity recognition. Science China Information Science, 63(10):2020. [[文件:Hierarchical LSTM with char-subword-word tree-structure representation for Chinese named entity recognition.pdf]] | ||
2020年10月5日 (一) 08:28的版本
请大家按照规则不断完善此页面。包含pdf ppt codes等。论文按年度，先中文、再英文；先期刊、再会议；先录用时间、后发表（开会）时间。尽量用英文吧。
文献格式和内容与内部wiki保持一致（尽量避免重复劳动）
- pdf ppt等附件都可以放到外网可以访问的地方，放一个地方，避免重复
- 基金号等信息，这个页面上删掉，不要写
2020
Talks and Misc.
- 2020.8.15: I have given a talk on data annotation at AI+EDUCATION SUB-FORUM at AI-EXPO (2020 GLOBAL AI PRODUCT AND APPLICATION EXPO)
Journal Papers in Chinese
Conference Papers in Chinese
Journal Papers In English
- 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, 63(10):2020. 文件:Hierarchical LSTM with char-subword-word tree-structure representation for Chinese named entity recognition.pdf
Conference Papers In English
- 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. pdf 文件:Zhangbo-acl2020-ppt-5-24.pdf
- 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. *-*. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. PDF (best paper!)
- Yu Zhao, Mingyue Zhou, Zhenghua Li, and Min Zhang. Dependency Parsing with Noisy Multi-Annotation Data. Proceedings of NLPCC-2020, pp. *-*. Zhengzhou, China, 14 Oct. - 18 Oct. 2020. PDF