I am currently a Ph.D. student in a joint program between the School of Advanced Interdisciplinary Sciences and the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, majoring in Computer Science and Technology. I am expected to graduate in 2028. My research interests focus on Large Language Models, Multi-Agent Systems, Misinformation Detection, and Knowledge Graph.
Outside of research, I am also a Top 500 Tank player in Overwatch — 汉什么森#5664 
🔥 News
- 2026.8: One paper titled “Beyond Factual Knowledge: Benchmarking and Learning Step-Level Procedural Rule Reasoning in Large Language Models” has been accepted by EMNLP 2026.
- 2026.1: One paper titled “Beyond Detection: Exploring Evidence-based Multi-Agent Debate for Misinformation Intervention and Persuasion” has been accepted by AAAI 2026 (Oral). First-time Oral Link, 50:00
- 2025.9: One paper titled “Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models” has been accepted by EMNLP 2025.
- 2025.9: One paper titled “DocPolicyKG: A Lightweight LLM-Based Framework for Knowledge Graph Construction from Chinese Policy Documents” has been accepted by CIKM 2025.
📝 Latest Publications
Chen Han, Yijia Ma, Jin Tan, Wenzhen Zheng, Xijin Tang
- Proposed an Evidence-based Multi-Agent Debate (ED2D) framework to address LLM hallucinations by introducing an Evidence Function Call for retrieving external knowledge (Wikipedia).
- Demonstrated that ED2D not only detects misinformation but also serves as a persuasive system to correct user misconceptions.
Chen Han, Wenzhen Zheng, Xijin Tang
- Reformulated misinformation detection as a multi-agent debate task, simulating real-world fact-checking processes to enhance reasoning interpretability and transparency.
- Outperformed existing baselines on two mainstream fake news datasets.
Chen Han, Yuanyuan Li, Xijin Tang
- Fine-tuned DeepSeek-R1-7B locally using LoRA and Few-shot learning to construct the first government investment promotion knowledge graph.
- Implemented a Graph-RAG architecture using Neo4J and Milvus for parallel retrieval to enable high-quality intelligent policy Q&A.
💻 Internships
- 2026.03 - Present, 小红书ACE顶尖实习生（Xiaohongshu ACE Top Intern）, Beijing. Position: Data Engineer Agent R&D
- 2025.10 - 2025.11, 蚂蚁集团（Ant Group）, Beijing. Position: LLM Algorithm Intern (Post-training & Evaluation).
- 2022.07 - 2023.05, 源码资本（Source Code Capital）, Beijing. Position: Algorithm Intern.
📖 Educations
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2025.02 – 2028.02, Ph.D., School of Advanced Interdisciplinary Sciences, University of Chinese Academy of Sciences (Advisor: Xijin Tang)
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2023.09 – 2025.02, M.S., Academy of Mathematics and Systems Science, Chinese Academy of Sciences (Advisor: Xijin Tang)
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2019.09 – 2023.06, B.S., Central University of Finance and Economics (Advisor: Lu Wei)
🧑⚖️ Academic Service
- Journal Reviewer: Computing Surveys(JCR Q1); ACM Transactions on Intelligent Systems and Technology (JCR Q1); International Journal of Human–Computer Interaction (JCR Q1); Frontiers in Psychology (JCR Q1);
- Conference Reviewer: AAAI (CCF-A); CIKM (CCF-B); KSS (Springer CCIS).
🎖 Honors and Awards
- 2026 入选小红书ACE顶尖实习生人才计划
- 2025 中国科学院大学比亚迪奖学金
- 2025 入选中国科协青年科技人才培育工程博士生专项计划
- 2024 Merit Student and Outstanding Student Leader, UCAS（中国科学院大学三好学生、优秀学生干部）
- 2023 Outstanding Graduate and Outstanding Undergraduate Thesis, CUFE (中央财经大学优秀毕业生、优秀毕业论文)
- 2022 National Undergraduate Innovation and Entrepreneurship Training Program（国家级大学生创新创业训练项目优秀结项）
- 2022 Second Prize, MathorCup University Mathematical Modeling Challenge（MathorCup高校数学建模挑战赛大数据竞赛二等奖）
- 2021 First Prize, Mathematical Contest in Modeling (MCM/ICM) （美国大学生数学建模竞赛一等奖）
- 2020–2023 中央财经大学三好学生
📚 All My Publications
2026
Yu, B., Cao, P., Han, C., Zhou, C., Zhang, Z., Xie, Z., Teng, W., Liao, X., Zhao, J., & Liu, K. (2026). Beyond factual knowledge: Benchmarking and learning step-level procedural rule reasoning in large language models. Findings of the Association for Computational Linguistics: EMNLP 2026. https://arxiv.org/abs/2608.22753
Han, C., Ma, Y., Tan, J., & Tang, X. (2026). Beyond detection: Exploring evidence-based multi-agent debate for misinformation intervention and persuasion. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2026 Oral). https://ojs.aaai.org/index.php/AAAI/article/view/41196
2025
Han, C., & Tang, X. (2025). An agent-based simulation framework for misinformation susceptibility test with LLMs: Insights from psychological factors. In Knowledge and Systems Sciences (pp. 289–302). Springer, Singapore. https://doi.org/10.1007/978-981-95-4990-0_25
Han, C., Zheng, W., & Tang, X. (2025). Debate-to-detect: Reformulating misinformation detection as a real-world debate with large language models. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (pp. 15114–15129). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.emnlp-main.764
Han, C., Li, Y., & Tang, X. (2025). DocPolicyKG: A lightweight LLM-based framework for knowledge graph construction from Chinese policy documents. In Proceedings of the 34th ACM International Conference on Information and Knowledge Management (pp. 4753–4757). https://doi.org/10.1145/3746252.3760904
韩晨, 唐锡晋. ACM TechNews中虚假信息报道发展进程研究—基于科技新闻的文本挖掘分析. 系统科学与数学, 2025. https://doi.org/10.12341/jssms250173 (Han, C., & Tang, X. (2025). Research on the development of disinformation reports in ACM TechNews: A text mining analysis based on technology news. Journal of Systems Science and Mathematical Sciences.)
Before 2023
Han, C., Wu, C., & Wei, L. (2023). The impact of the disclosure characteristics of the application material on the successful listing of companies on China’s Science and Technology Innovation Board. Journal of Behavioral and Experimental Finance, 37, 100733.
Chen, N., Han, C., & Wei, L. (2023). The impact of subjective and objective inconsistencies in scientific and technological innovation attributes on the listing of enterprises on the Science and Technology Innovation Board. Procedia Computer Science, 221, 493–500.
Wei, L., Deng, Y., Huang, J., Han, C., & Jing, Z. (2022). Identification and analysis of financial technology risk factors based on textual risk disclosures. Journal of Theoretical and Applied Electronic Commerce Research, 17(2), 590–612.
Wei, L., Han, C., & Yao, Y. (2022). The bias analysis of oil and gas companies’ credit ratings based on textual risk disclosures. Energies, 15(7), 2390.
Han, C., Liang, D., Huang, J., & Wei, L. (2022). The impact of disclosure characteristics of the registration statement for Science and Technology Innovation Board on the IPO underpricing. Procedia Computer Science, 199, 238–245.