简历 | 张兴华

研究兴趣

大模型对齐，长链推理，评估，强化学习，低资源学习等

简介

我目前任职于 阿里巴巴通义实验室，主要研究方向包括 大模型对齐、推理与评测，智能体强化学习，负责业务模型的后训练。博士毕业于中国科学院信息工程研究所，本科毕业于哈尔滨工业大学。

在包括ICLR、ACL、SIGIR、KDD、ICDE、WWW、TOIS、TACL、EMNLP 等在内的顶级国际会议和期刊上发表30+篇论文。如您对相关内容感兴趣，欢迎与我联系或进一步交流。

教育经历

工学博士，中国科学院大学/中国科学院信息工程研究所北京，2019.09 至 2024.06

专业：计算机应用技术

导师/指导教师：柳厅文研究员、许洪波研究员

GPA: 3.9/4.0

工学学士，哈尔滨工业大学哈尔滨，2015.09 至 2019.06

专业：计算机科学与技术

学分绩：92.11/100

论文列表

‡ 项目指导, * 通讯作者, † 共一

后训练 & 强化学习

Ruoran Li, Xinghua Zhang‡, Haiyang Yu, Shitong Duan, Xiang Li, Wenxin Xiang, Chonghua Liao, Xudong Guo, Yongbin Li, Jinli Suo. MemPO: Self-Memory Policy Optimization for Long-Horizon Agents . The 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), July 2026.

Shipeng Li†, Shikun Li†, Zhiqin Yang†, Xinghua Zhang, Gaode Chen, Xiaobo Xia, Hengyu Liu, Zhe Peng. LearnAlign: Reasoning Data Selection for Reinforcement Learning in Large Language Models Based on Improved Gradient Alignment . The 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), July 2026.

Minzheng Wang, Yongbin Li, Haobo Wang, Xinghua Zhang*‡, Nan Xu, Bingli Wu, Fei Huang, Haiyang Yu, Wenji Mao*. Adaptive Social Learning via Mode Policy Optimization for Language Agents . The Fourteenth International Conference on Learning Representations (ICLR 2026), April 2026.

Tao Zou, Xinghua Zhang‡, Haiyang Yu, Minzheng Wang, Fei Huang, Yongbin Li. EIFBench: Extremely Complex Instruction Following Benchmark for Large Language Models . Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025 main), November 2025.

Xinghua Zhang, Haiyang Yu, Cheng Fu, Fei Huang, Yongbin Li. IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization . The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025 main), July 2025.

Minzheng Wang, Xinghua Zhang‡, Kun Chen, Nan Xu, Haiyang Yu, Fei Huang, Wenji Mao, Yongbin Li. Reframing Dialogue Interaction with Fine-grained Element Modeling . The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), July 2025.

大模型Benchmark，评估 & 测试时优化

Wenyuan Zhang†, Shuaiyi Nie†, Xinghua Zhang‡, Zefeng Zhang, Tingwen Liu. S1-Bench: A Simple Benchmark for Evaluating System 1 Thinking Capability of Large Reasoning Models . The 35th International Joint Conference on Artificial Intelligence (IJCAI 2026), August 2026.

Wenyuan Zhang, Xinghua Zhang‡, Haiyang Yu, Shuaiyi Nie, Bingli Wu, Juwei Yue, Tingwen Liu, Yongbin Li. ExpSeek: Self-Triggered Experience Seeking for Web Agents . The 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), July 2026.

Wenyuan Zhang, Jiawei Sheng, Shuaiyi Nie, Zefeng Zhang, Xinghua Zhang, Yongquan He, Tingwen Liu. Revealing and Mitigating the Challenge of Detecting Character Knowledge Errors in LLM Role-Playing . Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025 main), November 2025.

Xinghua Zhang, Bowen Yu, Haiyang Yu, Yangyu Lv, Tingwen Liu, Fei Huang, Hongbo Xu and Yongbin Li. Wider and Deeper LLM Networks are Fairer LLM Evaluators . Transactions of the Association for Computational Linguistics (TACL, Oral@ACL 2025). 2025.

Xiang Li, Haiyang Yu, Xinghua Zhang, Ziyang Huang, Shizhu He, Kang Liu, Jun Zhao, Fei Huang, Yongbin Li. SOCRATIC-PRMBENCH: Benchmarking Process Reward Models with Systematic Reasoning Patterns . arXiv preprint arXiv:2505.23474.

Minzheng Wang†, Longze Chen†, Cheng Fu, Shengyi Liao, Xinghua Zhang, Bingli Wu, Haiyang Yu, Nan Xu, Lei Zhang, Run Luo, Yunshui Li, Min Yang, Fei Huang, Yongbin Li. Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA . The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024, Oral), November 2024.

Xinghua Zhang, Haiyang Yu, Yongbin Li, Minzheng Wang, Longze Chen, Fei Huang. The Imperative of Conversation Analysis in the era of LLMs: A Survey of Tasks, Techniques, and Trends . arXiv preprint arXiv:2409.14195.

Mengyao Chen, Xinghua Zhang, Junhao Zhang, Quangang Li, Tingwen Liu. Empowering LLMs for Multi-Page Layout Generation via Consistency-Oriented In-Context Learning . In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), October 2024.

大模型安全

Zhenhong Zhou, Haiyang Yu, Xinghua Zhang, Rongwu Xu, Fei Huang, Kun Wang, Yang Liu, Junfeng Fang, Yongbin Li. On the Role of Attention Heads in Large Language Model Safety . The Thirteenth International Conference on Learning Representations (ICLR, Oral), April 2025.

Zhenhong Zhou, Haiyang Yu, Xinghua Zhang, Rongwu Xu, Fei Huang, Yongbin Li. How Alignment and Jailbreak Work: Explain LLM Safety through Intermediate Hidden States . The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), November 2024.

信息抽取 & 语义理解

Xinghua Zhang, Gaode Chen, Shiyao Cui, Jiawei Sheng, Tingwen Liu and Hongbo Xu. Exogenous and Endogenous Data Augmentation for Low-Resource Complex Named Entity Recognition . In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024), July 2024.

Minghuan Yuan, Shiyao Cui, Xinghua Zhang, Shicheng Wang, Hongbo Xu and Tingwen Liu. Exploring the Trade-Off within Visual Information for MultiModal Sentence Summarization . In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024), July 2024.

Xinghua Zhang, Bowen Yu, Xin Cong, Taoyu Su, Quangang Li, Tingwen Liu and Hongbo Xu. Cross-domain NER under a Divide-and-Transfer Paradigm . In ACM Transactions on Information Systems (TOIS 2024), April 2024.

Wenyuan Zhang, Xinghua Zhang, Shiyao Cui, Kun Huang, Xuebin Wang and Tingwen Liu. Adaptive Data Augmentation for Aspect Sentiment Quad Prediction . In 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024), April 2024.

Wenhao Zhang, Shiyao Cui, Wenyuan Zhang, Xinghua Zhang, Tingwen Liu and Hongbo Xu. Improving Chinese Spelling Correction With Text-Phonetics Differentiation and Adaptive Fusion . In 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024), April 2024.

Kun Huang, Yongxiu Xu, Xinghua Zhang, Wenyuan Zhang and Hongbo Xu. Prompting Generative Language Model with Guiding Augmentation for Aspect Sentiment Triplet Extraction . In Pacific Rim International Conference on Artificial Intelligence (PRICAI 2023), November 2023.

Tianyun Liu, Xinghua Zhang, Zhenyu Zhang, Yubin Wang, Quangang Li, Shuai Zhang and Tingwen Liu. Enhancing Table Retrieval with Dual Graph Representations . In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2023 (ECML PKDD 2023), September 2023.

Xinghua Zhang, Tianyun Liu, Wenyuan Zhang and Tingwen Liu. System Report for CCL23-Eval Task 1: Information Theory Constraint and Paragraph based Classical Named Entity Recognition . In Proceedings of the 22nd Chinese National Conference on Computational Linguistics (CCL 2023), August 2023.

Xinghua Zhang, Bowen Yu, Jiangxia Cao, Quangang Li, Xuebin Wang, Tingwen Liu and Hongbo Xu. Representation and Labeling Gap Bridging for Cross-lingual Named Entity Recognition . In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023), July 2023.

Xinghua Zhang, Bowen Yu, Tingwen Liu, Yubin Wang, Taoyu Su and Hongbo Xu. Exploring Modular Task Decomposition in Cross-domain Named Entity Recognition . In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022), July 2022.

Zhaohui Wang, Xinghua Zhang, Yanzeng Li, Yubin Wang, Jiawei Sheng, Tingwen Liu and Hongbo Xu. Enhancing Pre-Trained Language Representations Based on Contrastive Learning for Unsupervised Keyphrase Extraction . In Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering (SEKE 2022), July 2022.

Xinghua Zhang, Bowen Yu, Tingwen Liu, Zhenyu Zhang, Jiawei Sheng, Mengge Xue and Hongbo Xu. Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising Learning . In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), November 2021.

后训练 & 强化学习

大模型Benchmark，评估 & 测试时优化

大模型安全

信息抽取 & 语义理解

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