姓名：关勇
职称：讲师
研究方向（Focus Area）：
1、大模型智能体
2、大模型机理分析
3、自然语言处理
4、知识工程
联系方式
办公地址：主楼 E521
电子邮箱：yongguan@ncepu.edu.cn
一、个人简介及主要荣誉称号
关勇，男，中共党员。2022年博士毕业，随后于清华大学计算机系KEG实验室进行博士后研究工作。2025年入职华北电力大学。主要从事自然语言处理、知识工程等领域的研究工作。主持国家自然科学基金青年项目1项，参与国家863计划、国家重点研发、国自然重点等国家级项目。在WWW、ACL、AAAI、EMNLP、COLING等国际国内重要会议和期刊发表一作论文10余篇，申请发明专利10余项，其中授权5项。
团队长期招收硕士研究生、实习生，欢迎感兴趣的同学加入！
二、主要科研项目情况
[1] 国家自然科学基金青年项目, 基于检索增强的可解释性事件预测关键技术研究, 2025-2027, 主持
[2] 北京市自然科学基金—小米联合基金重点项目, 大语言模型知识的表征、学习、记忆和注入机制分析与验证, 2024-2026, 参与
[3] 国强研究院人工智能与机器人领域基础研究项目, 大规模常识库的构建、表征、推理方法及开放平台, 2019-2024, 参与
[4] 国家重点研发计划项目子课题, 面向分析师的知识工程技术, 2022-2024, 参与
[5] 国家自然科学基金重点项目, 基于语言认知机理的汉语框架语义计算研究, 2020-2024, 参与
三、代表性论著
[1] Yong Guan, Dingxiao Liu, Jinchen Ma, Hao Peng, Xiaozhi Wang, Lei Hou, Ru Li. Event GDR: Event-Centric Generative Document Retrieval [C]. In Proceedings of the ACM on Web Conference. (WWW2024)
[2] Yong Guan, Freddy Lecue, Jiaoyan Chen, Ru Li, Jeff Z. Pan. Knowledge-Aware Neuron Interpretation for Scene Classification [C]. In Proceedings of the AAAI Conference on Artificial Intelligence. (AAAI2024)
[3] Yong Guan, Jiaoyan Chen, Freddy Lecue, Jeff Z. Pan, Juanzi Li, Ru Li. Trigger-Argument based Explanation for Event Detection [C]. Findings of the Association for Computational Linguistics. (Findings of ACL2023)
[4] Yong Guan, Hao Peng, Lei Hou, Juanzi Li. MMD-ERE: Multi-Agent Multi-Sided Debate for Event Relation Extraction [C]. The 31st International Conference on Computational Linguistics. (COLING2025)
[5] Yong Guan, Xiaozhi Wang, Lei Hou, Juanzi Li, Jeff Z. Pan, Jiaoyan Chen, Freddy Lecue. TacoERE: Cluster-aware Compression for Event Relation Extraction [C]. In Proceedings of the 2024 Joint International Conference on Computational Linguistics. (COLING2024)
[6] Yong Guan, Shaoru Guo, Ru Li, Xiaoli Li, Hongye Tan. Frame semantic-enhanced sentence modeling for sentence-level extractive text summarization [C]. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. (EMNLP2021)
[7] Yong Guan, Shaoru Guo, Ru Li, Xiaoli Li, Hu Zhang. Integrating semantic scenario and word relations for abstractive sentence summarization [C]. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. (EMNLP2021)
[8] Yong Guan, Shaoru Guo, Ru Li, Xiaoli Li, Hu Zhang. Frame semantics guided network for abstractive sentence summarization [J]. Knowledge-Based Systems. 2021, 221:106973.
[9] Yong Guan, Shaoru Guo, Ru Li. Structure-to-Word Dynamic Interaction Model for Abstractive Sentence Summarization [J]. Neural Computing and Applications.
[10] Yong Guan, Ru Li, Shaoru Guo. What Linguistic Information Does Reading Comprehension Require? [C]. The China Conference on Knowledge Graph and Semantic Computing. (CCKS2020)