论文

共 132 篇。带「解读」链接的条目有解读文字。

arXiv 论文 (18)

[arXiv 2026] Zheng Fang, Yongmin Li, Yichang Zhang, Dongming Jin, Haoyu Wang, Shuai Wang, Zhi Jin, Ge Li; CONTRA: Discovering and Qualifying Behavior-Changing Questions for Selective Clarification in LLM Code Generation; arXiv preprint, arXiv:2610.01769, 2026. PDF 代码
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[arXiv 2026] Yihong Dong, Jianha Xiao, Xue Jiang, Xuyuan Guo, Zhiyuan Fan, Jiaru Qian, Kechi Zhang, Jia Li, Zhi Jin, Ge Li; Evaluating the Formal Reasoning Capabilities of Large Language Models through Chomsky Hierarchy; arXiv preprint, arXiv:2604.02709, 2026. PDF
[arXiv 2026] Huanyu Liu, Ge Li, Yihong Dong, Sihan Wu, Peixu Wang, Sihao Cheng, Taozhi Chen, Kechi Zhang, Hao Zhu, Tongxuan Liu; Do Transformers Have the Ability for Periodicity Generalization?; arXiv preprint, arXiv:2601.22690, 2026. PDF
[arXiv 2025] Jia Li, Xianjie Shi, Kechi Zhang, Lei Li, Ge Li, Zhengwei Tao, Fang Liu, Chongyang Tao, Zhi Jin; CodeRAG: Supportive Code Retrieval on Bigraph for Real-World Code Generation; arXiv preprint, arXiv:2504.10046, 2025. PDF
[arXiv 2025] Yuqi Zhu, Ge Li, Xue Jiang, Jia Li, Hong Mei, Zhi Jin, Yihong Dong; Uncertainty-Guided Chain-of-Thought for Code Generation with LLMs; arXiv preprint, arXiv:2503.15341, 2025. PDF

已发表论文 (114)

[ICSE 2027] Xue Jiang, Tianyu Zhang, Lingwei Wu, Ziyu Wang, Ge Li, Yuan Sui, Hao Zhu, Wenpin Jiao, Zhi Jin, Yihong Dong; PRAXIS: Graph-Grounded Tacit Knowledge for Domain Code Generation; IEEE/ACM International Conference on Software Engineering.
[软件学报, 2026] Yihong Dong, Xue Jiang, Jiaru Qian, Tian Wang, Kechi Zhang, Zhi Jin, Ge Li; 基于大语言模型智能体的代码生成综述（A Survey on Code Generation with LLM-based Agents）; 软件学报 (软件学报); Vol. 37, Iss. 8, pp.3089-3115. PDF
[AAAI 2026] Xue Jiang, Yihong Dong, Zheng Fang, Yingwei Ma, Tangxinyu Wang, Rongyu Cao, Binhua Li, Zhi Jin, Wenpin Jiao, Yongbin Li, Ge Li; Large Language Model Unlearning for Source Code; The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026), Singapore, Singapore. PDF
[ISSTA 2026] Yongmin Li, Yihong Dong, Jia Li, Ge Li; Efficient Grammar-Constrained Decoding via Parser Stack Classification; The ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2026), Oakland, California, USA, October 4 - 9, 2026.
[SCIS, 2026] Fang Liu, Ge Li, Qianhui Zhao, Li Zhang; Learning to Represent Code Semantics; Science China Information Sciences (SCIS); Vol. 68, Iss. 7, pp.172101:1-172101:21.
[ACL 2026] Yihong Dong, Xue Jiang, Yongding Tao, Huanyu Liu, Kechi Zhang, Lili Mou, Rongyu Cao, Yingwei Ma, Jue Chen, Binhua Li, Zhi Jin, Fei Huang, Yongbin Li, Ge Li; Rl-plus: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization; Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), San Diego, California, USA, July 2 - 7, 2026. PDF
[ACL 2026] Yihong Dong, Zhaoyu Ma, Xue Jiang, Zhiyuan Fan, Jiaru Qian, Yongmin Li, Jianha Xiao, Zhi Jin, Rongyu Cao, Binhua Li, Fei Huang, Yongbin Li, Ge Li; Saber: Efficient Sampling with Adaptive Acceleration and Backtracking Enhanced Remasking for Diffusion Language Model in Code Generation; Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), San Diego, California, USA.
[FSE 2026] Yuqi Zhu, Ge Li, Hong Mei, Zhi Jin, Jia Li, Qibin Zheng, Jieyuan Zhang; Influence-Aware Bayesian-Inspired Token Reweighting for Improved Code Generation; Proceedings of the ACM International Conference on the Foundations of Software Engineering (FSE 2026), Montreal, Canada.
[FSE 2026] Hao Zhu, Jia Li, Cuiyun Gao, Jiaru Qian, Yihong Dong, Huanyu Liu, Lecheng Wang, Ziliang Wang, Xiaolong Hu, Ge Li; VulInstruct: Teaching LLMs Root-Cause Reasoning for Vulnerability Detection via Security Specifications; Proceedings of the ACM International Conference on the Foundations of Software Engineering (FSE 2026), Montreal, Canada.
[ICSE 2026] Yongmin Li, Jia Li, Ge Li, Zhi Jin; AdapTrack: Constrained Decoding without Distorting LLM's Output Intent; Proceedings of the 48th IEEE/ACM International Conference on Software Engineering (ICSE 2026), Rio de Janeiro, Brazil.
[ICSE 2026] Kechi Zhang, Huangzhao Zhang, Ge Li, Jinliang You, Jia Li, Yunfei Zhao, Zhi Jin; SEAlign: Alignment Training for Software Engineering Agent; Proceedings of the 48th IEEE/ACM International Conference on Software Engineering (ICSE 2026), Rio de Janeiro, Brazil. PDF
[ACL 2026] Huanyu Liu, Jia Li, Chang Yu, Taozhi Chen, Yihong Dong, Lecheng Wang, Yongding Tao, Xiaolong Hu, Ge Li; EvoCoT: Overcoming the Exploration Bottleneck in Reinforcement Learning; Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), San Diego, California, USA. PDF
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[ICLR 2026] Yongding Tao, Tian Wang, Yihong Dong, Huanyu Liu, Kechi Zhang, Xiaolong Hu, Ge Li; Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models; Proceedings of the Fourteenth International Conference on Learning Representations (ICLR 2026), Rio de Janeiro, Brazil. PDF
[ACL 2026] Xue Jiang, Yihong Dong, Mengyang Liu, Hongyi Deng, Tian Wang, Yongding Tao, Rongyu Cao, Binhua Li, Zhi Jin, Wenpin Jiao, Fei Huang, Yongbin Li, Ge Li; CODERL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment; Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), San Diego, California, USA. PDF
[ACL 2026] Zheng Fang, Yihong Dong, Lili Mou, Dongming Jin, Zhi Jin, Ge Li; IntentCoding: Amplifying User Intent in Code Generation; Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), San Diego, California, USA. PDF
[ACL 2026] Xue Jiang, Ge Li, Jiaru Qian, Xianjie Shi, Chenjie Li, Hao Zhu, Ziyu Wang, Jielun Zhang, Zheyu Zhao, Lingwei Wu, Kechi Zhang, Jia Li, Wenpin Jiao, Zhi Jin, Yihong Dong; KOCO-BENCH: Can Large Language Models Leverage Domain Knowledge in Software Development?; Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), San Diego, California, USA. PDF
[TOSEM, 2025] Jia Li, Ge Li, Yongmin Li, Jin Zhi; Structured Chain-of-Thought Prompting for Code Generation; ACM Transactions on Software Engineering and Methodology (TOSEM); Vol. 34, Iss. 2, pp.1-23.
[TOSEM, 2025] Yuwei Zhang, Zhi Jin, Ying Xing, Ge Li, Fang Liu, Jiaxin Zhu, Wensheng Dou, Jun Wei; PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing; ACM Transactions on Software Engineering and Methodology.
[EMSE, 2025] Jia Li, Zheng Fang, Xianjie Shi, Zhi Jin, Fang Liu, Yunfei Zhao, Ge Li; SCodeSearcher: Soft Contrastive Learning for Code Search; Empirical Software Engineering (EMSE); Vol. 30, Iss. 3, pp.1-23.
[EMSE, 2025] Kechi Zhang, Jia Li, Zhuo Li, Zhi Jin, Ge Li; Transformer-based Code Model with Compressed Hierarchy Representation; Empirical Software Engineering (EMSE); Vol. 30, Iss. 2, pp.1-43.
[ICSE 2025] Xue Jiang, Yihong Dong, Yongding Tao, Huanyu Liu, Zhi Jin, Ge Li; ROCODE: Integrating Backtracking Mechanism and Program Analysis in Large Language Models for Code Generation; Proceedings of the 47th IEEE/ACM International Conference on Software Engineering (ICSE 2025), Ottawa, Ontario, Canada.
[ICSE 2025] Siyuan Jiang, Jia Li, He Zong, Huanyu Liu, Hao Zhu, Shukai Hu, Erlu Li, Jiazheng Ding, Yu Han, Wei Ning, Ge Li; aiXcoder-7B: A Lightweight and Effective Large Language Model for Code Completion; Proceedings of the 47th IEEE/ACM International Conference on Software Engineering (ICSE 2025), Ottawa, Ontario, Canada.
[TOSEM, 2025] Jia Li, Chongyang Tao, Jia Li, Ge Li, Zhi Jin, Huangzhao Zhang, Zheng Fang, Fang Liu; Large language Model-aware in-Context Learning for Code Generation; ACM Transactions on Software Engineering and Methodology (TOSEM); Vol. 34, Iss. 7, pp.1-33.
[ACL 2025] Jia Li, Xuyuan Guo, Lei Li, Kechi Zhang, Ge Li, Jia Li, Zhengwei Tao, Fang Liu, Chongyang Tao, Yuqi Zhu, Zhi Jin; Benchmarking Long-Context Language Models on Long Code Understanding; Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria.
[ACL 2025] Kaibo Liu, Zhenpeng Chen, Yiyang Liu, Jie Zhang, Mark Harman, Yudong Han, Yun Ma, Yihong Dong, Ge Li, Gang Huang; LLM-Powered Test Case Generation for Detecting Bugs in Plausible Programs; Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria.
[ACL 2025] Kechi Zhang, Ge Li, Jia Li, Yihong Dong, Jia Li, Zhi Jin; Focused-DPO: Enhancing Code Generation Through Focused Preference Optimization on Error-Prone Points; Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria.
[ACL 2025] Yihong Dong, Yuchen Liu, Xue Jiang, Zhi Jin, Ge Li; Rethinking Repetition Problems in Code Generation; Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria.
[ACL 2025] Kechi Zhang, Ge Li, Yihong Dong, Jingjing Xu, Jun Zhang, Jing Su, Yongfei Liu, Zhi Jin; CodeDPO: Aligning Code Models with Self Generated and Verified Source Code; Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria.
[ASE 2025] Jia Li, Hao Zhu, Huanyu Liu, Xianjie Shi, He Zong, Yihong Dong, Kechi Zhang, Siyuan Jiang, Zhi Jin, Ge Li; aiXcoder-7B-v2: Training LLMs to Fully Utilize the Long Context in Repository-level Code Completion; Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering (ASE 2025), Seoul, South Korea. PDF
[NeurIPS 2025] Yihong Dong, Ge Li, Yongding Tao, Xue Jiang, Kechi Zhang, Jia Li, Jing Su, Jun Zhang, Jingjing Xu; FAN: Fourier Analysis Networks; Proceedings of the 39th Annual Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, USA. PDF