基本信息
张元哲 男 中国科学院自动化研究所
电子邮件： yuanzhe.zhang@ia.ac.cn
通信地址： 北京市海淀区中关村东路95号
邮政编码： 100190
电子邮件： yuanzhe.zhang@ia.ac.cn
通信地址： 北京市海淀区中关村东路95号
邮政编码： 100190
招生信息
招生专业
081104-模式识别与智能系统
081203-计算机应用技术
081203-计算机应用技术
招生方向
自然语言处理，知识工程，可解释性研究
教育背景
2011-09--2016-07 中国科学院自动化研究所 博士
2007-09--2011-06 北京航空航天大学 学士
2007-09--2011-06 北京航空航天大学 学士
工作经历
工作简历
2020-10~现在, 中国科学院自动化研究所, 副研究员
2020-08~2020-10,中国科学院自动化研究所, 助理研究员
2018-08~2020-08,中国科学院自动化研究所, 博士后
2016-07~2018-07,百度, 自然语言处理高级工程师
2020-08~2020-10,中国科学院自动化研究所, 助理研究员
2018-08~2020-08,中国科学院自动化研究所, 博士后
2016-07~2018-07,百度, 自然语言处理高级工程师
社会兼职
2020-11-01-今,中文信息学会青年工作委员会委员,
2018-12-01-今,中文信息学会医疗健康与生物信息处理专业委员会委员,
2018-12-01-今,中文信息学会医疗健康与生物信息处理专业委员会委员,
教授课程
信息检索
知识图谱
知识图谱
专利与奖励
奖励信息
（1） 北京市科学技术进步奖一等奖, 一等奖, 省级, 2019
专利成果
[1] 刘康, 张元哲, 赵军, 许豹. 篇章级关系抽取方法、装置、电子设备及存储介质. CN: CN115618846A, 2023-01-17.
[2] 张元哲, 刘康, 赵军, 杨朝. 归因解释方法的稳定性的确定方法、装置和设备. CN: CN115422921A, 2022-12-02.
[3] 刘康, 张元哲, 赵军, 杨朝. 解释指导的知识蒸馏方法、装置、电子设备及存储介质. CN: CN115481740A, 2022-12-16.
[4] 刘康, 张元哲, 赵军, 丘德来. 基于外部知识增强的机器阅读理解方法、系统、装置. CN: CN111078836B, 2023-08-08.
[5] 刘康, 张元哲, 赵军, 丘德来. 基于外部知识增强的机器阅读理解方法、系统、装置. CN: CN111078836A, 2020-04-28.
[6] 赵军, 张元哲, 刘康, 田志兴. 基于图网络的答案句选择方法及装置. CN: CN110941962B, 2021-09-28.
[7] 刘康, 赵军, 徐立恒, 张元哲. 基于多知识库和整数线性规划ILP的自动问答方法和系统. CN: CN104820694A, 2015-08-05.
[2] 张元哲, 刘康, 赵军, 杨朝. 归因解释方法的稳定性的确定方法、装置和设备. CN: CN115422921A, 2022-12-02.
[3] 刘康, 张元哲, 赵军, 杨朝. 解释指导的知识蒸馏方法、装置、电子设备及存储介质. CN: CN115481740A, 2022-12-16.
[4] 刘康, 张元哲, 赵军, 丘德来. 基于外部知识增强的机器阅读理解方法、系统、装置. CN: CN111078836B, 2023-08-08.
[5] 刘康, 张元哲, 赵军, 丘德来. 基于外部知识增强的机器阅读理解方法、系统、装置. CN: CN111078836A, 2020-04-28.
[6] 赵军, 张元哲, 刘康, 田志兴. 基于图网络的答案句选择方法及装置. CN: CN110941962B, 2021-09-28.
[7] 刘康, 赵军, 徐立恒, 张元哲. 基于多知识库和整数线性规划ILP的自动问答方法和系统. CN: CN104820694A, 2015-08-05.
出版信息
发表论文
[1] Yang Zhao, Yuanzhe Zhang, Dianbo Sui, Yiming Ju, Jun Zhao, Kang Liu. Explanation Guided Knowledge Distillation for Pre-trained Language Model Compression. ACM Transactions on Asian and Low-Resource Language Information Processing[J]. 2024, 第 2 作者 通讯作者 23(2): 1-19,
[2] Zhao Yang, Yuanzhe Zhang, Dianbo Sui, Cao Liu, Jun Zhao, Kang Liu. Representative Demonstration Selection for In-Context Learning with Two-Stage Determinantal Point Process. Proceedings of the 2023 conference on empirical methods in natural language processing (EMNLP 2023). 2023, 第 2 作者
[3] Zhongtao Jiang, Yuanzhe Zhang, Liu Cao, Jun Zhao, Kang Liu. Generative Calibration for In-context Learning. Proceedings of the 2023 conference on empirical methods in natural language processing (EMNLP 2023, finding). 2023, 第 2 作者
[4] Yifan Wei, Yisong Su, Huanhuan Ma, Xiaoyan Yu, Fangyu Lei, Yuanzhe Zhang, Jun Zhao, Kang Liu. MenatQA: A New Dataset for Testing the Temporal Comprehension and Reasoning Abilities of Large Language Models. Proceedings of the 2023 conference on empirical methods in natural language processing (EMNLP 2023, finding). 2023, 第 6 作者
[5] Zhongtao Jiang, Yuanzhe Zhang, Liu Cao, Jiansong Chen, Jun Zhao, Kang Liu. Interpreting Sentiment Composition with Latent Semantic Tree. Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics（ACL 2023, finding）. 2023, 第 2 作者
[6] Yiming Ju, Yuanzhe Zhang, Zhao Yang, Zhongtao Jiang, Kang Liu, Jun Zhao. Logic Traps in Evaluating Attribution Scores. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics（ACL 2022）. 2022, 第 2 作者
[7] Zhao Yang, Yuanzhe Zhang, Zhongtao Jiang, Yiming Ju, Jun Zhao, Kang Liu. Can We Really Trust Explanations? Evaluating the Stability of Feature Attribution Explanation Methods via Adversarial Attack. Proceedings of the 21st Chinese National Conference on Computational Linguistics (CCL 2022). 2022, 第 2 作者
[8] Yiming Ju, Weikang Wang, Yuanzhe Zhang, Suncong Zheng, Kang Liu, Jun Zhao. CMQA: A Dataset of Conditional Question Answering with Multiple-Span Answers. Proceedings of the 29th International Conference on Computational Linguistics(COLING 2022). 2022, 第 3 作者
[9] 李泽政, 田志兴, 张元哲, 刘康, 赵军. 基于自适应知识选择的机器阅读理解. 中文信息学报[J]. 2021, 第 3 作者
[10] Yan, Cheng, Zhang, Yuanzhe, Liu, Kang, Zhao, Jun, Shi, Yafei, Liu, Shengping. Enhancing unsupervised medical entity linking with multi-instance learning. BMC MEDICAL INFORMATICS AND DECISION MAKING[J]. 2021, 第 2 作者 通讯作者 21(SUPPL 9): http://dx.doi.org/10.1186/s12911-021-01654-z.
[11] Cheng Yan, Yuanzhe Zhang, Kang Liu, Zhao Jun, Yafei Shi, Shengping Liu. Biomedical Concept Normalization by Leveraging Hypernyms. EMNLP-2021. 2021, 第 2 作者
[12] Zhixing Tian, Yuanzhe Zhang, Kang Liu, Jun Zhao. Topic Knowledge Acquisition and Utilization for Machine Reading Comprehension in Social Media Domain. CCL. 2021, 第 2 作者
[13] Yiming Ju, Yuanzhe Zhang, Zhixing Tian, Kang Liu, Xiaohuan Cao, Wenting Zhao, Jinlong Li, Zhao Jun. Enhancing Multiple-choice Machine Reading Comprehension by Punishing Illogical Interpretations. EMNLP-2021. 2021, 第 2 作者
[14] Zhongtao Jiang, Yuanzhe Zhang, Zhao Yang, Zhao Jun, Kang Liu. Alignment Rationale for Natural Language Inference. ACL-IJCNLP-2021. 2021, 第 2 作者
[15] Yuanzhe Zhang, Zhongtao Jiang, Tao Zhang, 刘诗万, Jiarun Cao, Kang Liu, Shengping Liu, Zhao, Jun. MIE: A Medical Information Extractor towards Medical Dialogues. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics(ACL 2020). 2020, 第 1 作者
[16] 田志兴, Yuanzhe Zhang, Yuanzhe Zhang, Xinwei Feng, Wenbin Jiang, Yajuan Lyu, Kang Liu, Zhao Jun. Capturing Sentence Relations for Answer Sentence Selection with Multi-Perspective Graph Encoding. The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020). 2020, 第 2 作者
[17] 田志兴, Yuanzhe Zhang, Kang Liu, Jun ZHAO, Yantao Jia, Zhicheng Sheng. Scene Restoring for Narrative Machine Reading Comprehension. The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020). 2020, 第 2 作者
[18] Zhao Jun. Machine Reading Comprehension Using Structural Knowledge Graph-aware Network. EMNLP 2019（CCF B）. 2019,
[19] 刘树林, 王雪鹏, 刘康, 何世柱, 张元哲, 赵军. 基于网络语义标签的多源知识库实体对齐算法. 计算机学报[J]. 2017, 第 5 作者40(3): 701-711, http://lib.cqvip.com/Qikan/Article/Detail?id=671454440.
[20] Zhao Jun, Hao Yanchao, Zhang Yuanzhe, Liu Kang, He Shizhu, Liu Zhanyi, Wu Hua. An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge. 2017, 第 3 作者http://ir.ia.ac.cn/handle/173211/20028.
[21] Liu Kang, Zhao Jun, Hao Yanchao, Zhang Yuanzhe, He Shizhu. A Joint Embedding Method for Entity Alignment of Knowledge Bases. KNOWLEDGE GRAPH AND SEMANTIC COMPUTING: SEMANTIC, KNOWLEDGE, AND LINKED BIG DATA. 2016, 第 4 作者650: 3-14,
[22] 刘康, 张元哲, 纪国良, 来斯惟, 赵军. 基于表示学习的知识库问答研究进展与展望. ACTA AUTOMATICA SINICA[J]. 2016, 第 2 作者42(42): 807-818,
[23] Zhang Yuanzhe, He Shizhu, Liu Kang, Zhao Jun, AAAI. A Joint Model for Question Answering over Multiple Knowledge Bases. THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE. 2016, 第 1 作者3094-3100, http://apps.webofknowledge.com/CitedFullRecord.do?product=UA&colName=WOS&SID=5CCFccWmJJRAuMzNPjj&search_mode=CitedFullRecord&isickref=WOS:000485474203019.
[24] Liu, Kang, Zhao, Jun, He, Shizhu, Zhang, Yuanzhe. Question Answering over Knowledge Bases. IEEE INTELLIGENT SYSTEMS[J]. 2015, 第 4 作者30(5): 26-35, http://ir.ia.ac.cn/handle/173211/9006.
[25] He Shizhu, Zhao Jun, Zhang Yuanzhe, Liu Kang. CASIA@ V2: A MLN-based Question Answering System over Linked Data. 2014, 第 3 作者http://ir.ia.ac.cn/handle/173211/20636.
[26] Siwei Lai, Shizhu He, Kang Liu, Jun Zhao, Xueqiang Lv, Xuepeng Wang, Yuanzhe Zhang. Ontology Matching with Word Embeddings. PROCEEDINGS OF CCL 2014. 2014, 第 7 作者http://ir.ia.ac.cn/handle/173211/11490.
[27] Yuanzhe Zhang, Jun Zhao, Kang Liu, Shizhu He, Xueqiang Lv, Xuepeng Wang. IAMA Results for OAEI 2013. OM-2013 PROCEEDINGS. 2013, 第 1 作者http://ir.ia.ac.cn/handle/173211/11491.
[2] Zhao Yang, Yuanzhe Zhang, Dianbo Sui, Cao Liu, Jun Zhao, Kang Liu. Representative Demonstration Selection for In-Context Learning with Two-Stage Determinantal Point Process. Proceedings of the 2023 conference on empirical methods in natural language processing (EMNLP 2023). 2023, 第 2 作者
[3] Zhongtao Jiang, Yuanzhe Zhang, Liu Cao, Jun Zhao, Kang Liu. Generative Calibration for In-context Learning. Proceedings of the 2023 conference on empirical methods in natural language processing (EMNLP 2023, finding). 2023, 第 2 作者
[4] Yifan Wei, Yisong Su, Huanhuan Ma, Xiaoyan Yu, Fangyu Lei, Yuanzhe Zhang, Jun Zhao, Kang Liu. MenatQA: A New Dataset for Testing the Temporal Comprehension and Reasoning Abilities of Large Language Models. Proceedings of the 2023 conference on empirical methods in natural language processing (EMNLP 2023, finding). 2023, 第 6 作者
[5] Zhongtao Jiang, Yuanzhe Zhang, Liu Cao, Jiansong Chen, Jun Zhao, Kang Liu. Interpreting Sentiment Composition with Latent Semantic Tree. Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics（ACL 2023, finding）. 2023, 第 2 作者
[6] Yiming Ju, Yuanzhe Zhang, Zhao Yang, Zhongtao Jiang, Kang Liu, Jun Zhao. Logic Traps in Evaluating Attribution Scores. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics（ACL 2022）. 2022, 第 2 作者
[7] Zhao Yang, Yuanzhe Zhang, Zhongtao Jiang, Yiming Ju, Jun Zhao, Kang Liu. Can We Really Trust Explanations? Evaluating the Stability of Feature Attribution Explanation Methods via Adversarial Attack. Proceedings of the 21st Chinese National Conference on Computational Linguistics (CCL 2022). 2022, 第 2 作者
[8] Yiming Ju, Weikang Wang, Yuanzhe Zhang, Suncong Zheng, Kang Liu, Jun Zhao. CMQA: A Dataset of Conditional Question Answering with Multiple-Span Answers. Proceedings of the 29th International Conference on Computational Linguistics(COLING 2022). 2022, 第 3 作者
[9] 李泽政, 田志兴, 张元哲, 刘康, 赵军. 基于自适应知识选择的机器阅读理解. 中文信息学报[J]. 2021, 第 3 作者
[10] Yan, Cheng, Zhang, Yuanzhe, Liu, Kang, Zhao, Jun, Shi, Yafei, Liu, Shengping. Enhancing unsupervised medical entity linking with multi-instance learning. BMC MEDICAL INFORMATICS AND DECISION MAKING[J]. 2021, 第 2 作者 通讯作者 21(SUPPL 9): http://dx.doi.org/10.1186/s12911-021-01654-z.
[11] Cheng Yan, Yuanzhe Zhang, Kang Liu, Zhao Jun, Yafei Shi, Shengping Liu. Biomedical Concept Normalization by Leveraging Hypernyms. EMNLP-2021. 2021, 第 2 作者
[12] Zhixing Tian, Yuanzhe Zhang, Kang Liu, Jun Zhao. Topic Knowledge Acquisition and Utilization for Machine Reading Comprehension in Social Media Domain. CCL. 2021, 第 2 作者
[13] Yiming Ju, Yuanzhe Zhang, Zhixing Tian, Kang Liu, Xiaohuan Cao, Wenting Zhao, Jinlong Li, Zhao Jun. Enhancing Multiple-choice Machine Reading Comprehension by Punishing Illogical Interpretations. EMNLP-2021. 2021, 第 2 作者
[14] Zhongtao Jiang, Yuanzhe Zhang, Zhao Yang, Zhao Jun, Kang Liu. Alignment Rationale for Natural Language Inference. ACL-IJCNLP-2021. 2021, 第 2 作者
[15] Yuanzhe Zhang, Zhongtao Jiang, Tao Zhang, 刘诗万, Jiarun Cao, Kang Liu, Shengping Liu, Zhao, Jun. MIE: A Medical Information Extractor towards Medical Dialogues. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics(ACL 2020). 2020, 第 1 作者
[16] 田志兴, Yuanzhe Zhang, Yuanzhe Zhang, Xinwei Feng, Wenbin Jiang, Yajuan Lyu, Kang Liu, Zhao Jun. Capturing Sentence Relations for Answer Sentence Selection with Multi-Perspective Graph Encoding. The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020). 2020, 第 2 作者
[17] 田志兴, Yuanzhe Zhang, Kang Liu, Jun ZHAO, Yantao Jia, Zhicheng Sheng. Scene Restoring for Narrative Machine Reading Comprehension. The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020). 2020, 第 2 作者
[18] Zhao Jun. Machine Reading Comprehension Using Structural Knowledge Graph-aware Network. EMNLP 2019（CCF B）. 2019,
[19] 刘树林, 王雪鹏, 刘康, 何世柱, 张元哲, 赵军. 基于网络语义标签的多源知识库实体对齐算法. 计算机学报[J]. 2017, 第 5 作者40(3): 701-711, http://lib.cqvip.com/Qikan/Article/Detail?id=671454440.
[20] Zhao Jun, Hao Yanchao, Zhang Yuanzhe, Liu Kang, He Shizhu, Liu Zhanyi, Wu Hua. An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge. 2017, 第 3 作者http://ir.ia.ac.cn/handle/173211/20028.
[21] Liu Kang, Zhao Jun, Hao Yanchao, Zhang Yuanzhe, He Shizhu. A Joint Embedding Method for Entity Alignment of Knowledge Bases. KNOWLEDGE GRAPH AND SEMANTIC COMPUTING: SEMANTIC, KNOWLEDGE, AND LINKED BIG DATA. 2016, 第 4 作者650: 3-14,
[22] 刘康, 张元哲, 纪国良, 来斯惟, 赵军. 基于表示学习的知识库问答研究进展与展望. ACTA AUTOMATICA SINICA[J]. 2016, 第 2 作者42(42): 807-818,
[23] Zhang Yuanzhe, He Shizhu, Liu Kang, Zhao Jun, AAAI. A Joint Model for Question Answering over Multiple Knowledge Bases. THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE. 2016, 第 1 作者3094-3100, http://apps.webofknowledge.com/CitedFullRecord.do?product=UA&colName=WOS&SID=5CCFccWmJJRAuMzNPjj&search_mode=CitedFullRecord&isickref=WOS:000485474203019.
[24] Liu, Kang, Zhao, Jun, He, Shizhu, Zhang, Yuanzhe. Question Answering over Knowledge Bases. IEEE INTELLIGENT SYSTEMS[J]. 2015, 第 4 作者30(5): 26-35, http://ir.ia.ac.cn/handle/173211/9006.
[25] He Shizhu, Zhao Jun, Zhang Yuanzhe, Liu Kang. CASIA@ V2: A MLN-based Question Answering System over Linked Data. 2014, 第 3 作者http://ir.ia.ac.cn/handle/173211/20636.
[26] Siwei Lai, Shizhu He, Kang Liu, Jun Zhao, Xueqiang Lv, Xuepeng Wang, Yuanzhe Zhang. Ontology Matching with Word Embeddings. PROCEEDINGS OF CCL 2014. 2014, 第 7 作者http://ir.ia.ac.cn/handle/173211/11490.
[27] Yuanzhe Zhang, Jun Zhao, Kang Liu, Shizhu He, Xueqiang Lv, Xuepeng Wang. IAMA Results for OAEI 2013. OM-2013 PROCEEDINGS. 2013, 第 1 作者http://ir.ia.ac.cn/handle/173211/11491.
发表著作
（1） 知识图谱：算法与实践, 高等教育出版社, 2022-03, 第 5 作者
科研活动
科研项目
（ 1 ） 面向文本问答的可解释性研究, 负责人, 国家任务, 2023-01--2026-12
（ 2 ） 嵌入知识组织体系的规模化领域预训练基础模型构建, 负责人, 国家任务, 2022-12--2025-11
（ 3 ） 医疗对话文本中的信息抽取关键技术研究, 负责人, 国家任务, 2020-01--2022-12
（ 4 ） 面向通用视觉的跨模态暗知识获取、融合与应用, 参与, 国家任务, 2023-01--2025-12
（ 5 ） 面向自然语言处理的可解释方法研究, 负责人, 企业委托, 2022-08--2023-08
（ 2 ） 嵌入知识组织体系的规模化领域预训练基础模型构建, 负责人, 国家任务, 2022-12--2025-11
（ 3 ） 医疗对话文本中的信息抽取关键技术研究, 负责人, 国家任务, 2020-01--2022-12
（ 4 ） 面向通用视觉的跨模态暗知识获取、融合与应用, 参与, 国家任务, 2023-01--2025-12
（ 5 ） 面向自然语言处理的可解释方法研究, 负责人, 企业委托, 2022-08--2023-08