* denotes the co-first authors

📝 Conference Papers

• A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning.
  Zhi Zhou, Yuhao Tan, Zenan Li, Yuan Yao, Lan-Zhe Guo, Yu-Feng Li, Xiaoxing Ma.
  In: Advances in Neural Information Processing Systems, San Diego, 2025.
  NeurIPS 2025. CCF-A. [Paper]

• VCSearch: Bridging the Gap Between Well-Defined and Ill-Defined Problems in Mathematical Reasoning.
  Shi-Yu Tian^*, Zhi Zhou^*, Kun-Yang Yu, Ming Yang, Lin-Han Jia, Lan-Zhe Guo, Yu-Feng Li.
  In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, Suzhou, 2025.
  EMNLP 2025. CCF-B, Oral Presentation.

• AutoEvolve: Automatically Evolving Queries for Applicable and Scalable Retrieval-Augmented Generation Benchmarking.
  Ding-Chu Zhang, Xiaowen Zhang, Yue Fei, Renjun Hu, Xiao-Wen Yang, Zhi Zhou, Baixuan Li, Yu-Feng Li, Xing Shi, Wei Lin.
  Findings @ EMNLP 2025.

• CGI: Identifying Conditional Generative Models with Example Images.
  Zhi Zhou^*, Hao-Zhe Tan^*, Peng-Xiao Song, Lan-Zhe Guo.
  In: Proceedings of the 34th International Joint Conference on Artificial Intelligence, Montreal, 2025.
  IJCAI 2025. CCF-A. [Paper] [Poster]

• Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models.
  Xiao-Wen Yang, Jie-Jing Shao, Lan-Zhe Guo, Bo-Wen Zhang, Zhi Zhou, Lin-Han Jia, Wang-Zhou Dai, Yu-Feng Li.
  In: Proceedings of the 34th International Joint Conference on Artificial Intelligence, Montreal, 2025.
  IJCAI 2025. CCF-A. [Paper]

• Fully Test-Time Adaptation for Feature Decrement in Tabular Data.
  Zi-Jian Cheng, Zi-Yi Jia, Kun-Yang Yu, Zhi Zhou, Lan-Zhe Guo.
  In: Proceedings of the 34th International Joint Conference on Artificial Intelligence, Montreal, 2025.
  IJCAI 2025. CCF-A.

• BMIP: Bi-directional Modality Interaction Prompt Learning for VLM.
  Song-Lin Lv, Yu-Yang Chen, Zhi Zhou, Ming Yang, Lan-Zhe Guo.
  In: Proceedings of the 34th International Joint Conference on Artificial Intelligence, Montreal, 2025.
  IJCAI 2025. CCF-A.

• Pre-Trained Vision-Language Model Selection and Reuse for Downstream Tasks.
  Hao-Zhe Tan, Zhi Zhou, Lan-Zhe Guo, Yu-feng Li.
  In: Proceedings of the 32nd International Conference on Machine Learning, Vancouver, 2025.
  ICML 2025. CCF-A. [Paper]

• TabFSBench: Tabular Benchmark for Feature Shifts in Open Environment.
  Zi-Jian Cheng, Ziyi Jia, Zhi Zhou, Lan-Zhe Guo, Yu-Feng Li.
  In: Proceedings of the 42nd International Conference on Machine Learning, Vancouver, 2025.
  ICML 2025. CCF-A. [Paper]

• LawGPT: Knowledge-Guided Data Generation and Its Application to Legal LLM
  Zhi Zhou^*, Kun-Yang Yu^*, Shi-Yu Tian^*, Xiao-Wen Yang^*, Jiang-Xin Shi^*, Peng-Xiao Song, Yi-Xuan Jin, Lan-Zhe Guo, Yu-Feng Li.
  SCI-FM Workshop @ ICLR 2025. [Paper]

• CARTS: Advancing Neural Theorem Proving with Diversified Tactic Calibration and Bias-Resistant Tree Search.
  Xiao-Wen Yang, Zhi Zhou, Haiming Wang, Aoxue Li, Wen-Da Wei, Hui Jin, Zhenguo Li, Yu-Feng Li.
  In: Proceedings of the 13th International Conference on Learning Representations, Singapore, 2025.
  ICLR 2025. CAAI-A. [Paper]

• Fully Test-time Adaptation for Tabular Data.
  Zhi Zhou^*, Kun-Yang Yu^*, Lan-Zhe Guo, Yu-Feng Li.
  In: Proceedings of the 39th AAAI conference on Artificial Intelligence, Philadelphia, 2025.
  AAAI 2025. CCF-A. [Paper] [Project] [Poster]

• Neuro-Symbolic Data Generation for Math Reasoning.
  Zenan Li^*, Zhi Zhou^*, Yuan Yao, Xian Zhang, Yu-Feng Li, Chun Cao, Fan Yang, Xiaoxing Ma.
  In: Advances in Neural Information Processing Systems, Vancouver, 2024.
  NeurIPS 2024. CCF-A. [Paper]

• LSPAN: Spectrally Localized Augmentation for Graph Consistency Learning.
  Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou, Yu-Feng Li.
  In: Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, Jeju, 2024. Page: 5462-5470.
  IJCAI 2024. CCF-A. [Paper]

• DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection.
  Zhi Zhou, Ming Yang, Jiang-Xin Shi, Lan-Zhe Guo, Yu-Feng Li.
  In: Proceedings of the 41th International Conference on Machine Learning, Vienna, 2024.
  ICML 2024. CCF-A. [Paper] [Code] [Poster]

• Long-tail Learning with Foundation Model: Heavy Fine-tuning Hurts.
  Jiang-Xin Shi, Tong Wei, Zhi Zhou, Jie-Jing Shao, Xin-Yan Han, Yu-Feng Li.
  In: Proceedings of the 41th International Conference on Machine Learning, Vienna, 2024.
  ICML 2024. CCF-A. [Paper]

• Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments.
  Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li.
  In: Proceedings of the 12th International Conference on Learning Representations, 2024.
  ICLR 2024. CAAI-A. [Paper]

• HONGAT: Graph Attention Networks in the Presence of High-Order Neighbors.
  Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou, Yu-Feng Li.
  In: Proceedings of the 38th AAAI conference on Artificial Intelligence, Vancouver, 2024. Page: 16750-16758.
  AAAI 2024. CCF-A. [Paper]

• Robust Test-Time Adaptation for Zero-Shot Prompt Tuning.
  Ding-Chu Zhang^*, Zhi Zhou^*, Yu-Feng Li.
  In: Proceedings of the 38th AAAI conference on Artificial Intelligence, Vancouver, 2024. Page: 16714-16722.
  AAAI 2024. CCF-A. [Paper] [Code] [Poster] [Slide]

• ODS: Test-Time Adaptation in the Presence of Open-World Data Shift.
  Zhi Zhou, Lan-Zhe Guo, Lin-Han Jia, Ding-Chu Zhang, Yu-Feng Li.
  In: Proceedings of the 40th International Conference on Machine Learning, Hawaii, 2023. Page: 42574-42588.
  ICML 2023. CCF-A, Oral Presentation. [Paper] [Code] [Poster] [Slide] [Video]

• Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions.
  Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Yu-Ke Xiang, Yu-Feng Li.
  In: Proceedings of the 40th International Conference on Machine Learning, Hawaii, 2023. Page: 14886-14901.
  ICML 2023. CCF-A, Oral Presentation. [Paper] [Code]

• Identifying Useful Learnwares for Heterogeneous Label Spaces.
  Lan-Zhe Guo^*, Zhi Zhou^*, Yu-Feng Li, Zhi-Hua Zhou.
  In: Proceedings of the 40th International Conference on Machine Learning, Hawaii, 2023. Page: 12122-12131.
  ICML 2023. CCF-A. [Paper] [Poster]

• You Only Submit One Image to Find the Most Suitable Generative Model
  Zhi Zhou, Lan-Zhe Guo, Pengxiao Song, Yu-Feng Li.
  Diffusion Workshop @ NeurIPS 2023. [Page] [Paper]

• USB: A Unified Semi-supervised Learning Benchmark for Classification.
  Yi-Dong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wen-Xin Hou, Ren-Jie Wang, Lin-Yi Yang, Zhi Zhou, Lan-Zhe Guo, He-Li Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jin-Dong Wang, Xing Xie, Yue Zhang.
  In: Advances in Neural Information Processing Systems Datasets and Benchmarks, New Orleans, LA, 2022. Page: 3938-3961.
  NeurIPS 2022 Datasets and Benchmarks. CCF-A. [Paper] [Code]

• STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data.
  Zhi Zhou^*, Lan-Zhe Guo^*, Zhan-Zhan Cheng, Yu-Feng Li, Shi-Liang Pu.
  In: Advances in Neural Information Processing Systems, Virtual Conference, 2021. Page: 29168-29180.
  NeurIPS 2021. CCF-A. [Paper] [Code] [Poster] [Slide]

• Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment.
  Lan-Zhe Guo^*, Zhi Zhou^*, Jie-Jing Shao, Yu-Feng Li, and DiDi Collaborators.
  In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Singapore, 2021. Page: 487-495.
  KDD 2021. CCF-A. [Paper]

• RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift.
  Lan-Zhe Guo, Zhi Zhou, and Yu-Feng Li.
  In: Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Diego, CA, 2020. Page: 1636-1644.
  KDD 2020. CCF-A. [Paper] [Code]

📖 Journal Papers

• Rts: Learning Robustly from Time Series Data with Noisy Label.
  Zhi Zhou, Yi-Xuan Jin, Yu-Feng Li.
  Frontiers of Computer Science, 18(6): 186332, 2024.
  FCS. CCF-B. [Paper] [Code]

• LAMDA-SSL: A Comprehensive Semi-Supervised Learning Toolkit.
  Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li.
  Science CHINA Information Science Letter, 67: 117101, 2024.
  SCIS Letter. CCF-A. [Arxiv] [Code]

• Towards Robust Test-Time Adaptation for Open-Set Recognition
  Zhi Zhou^*, Ding-Chu Zhang^*, Yu-Feng Li, Min-Ling Zhang.
  Journal of Software (软件学报), 35(4), 2024.
  JOS. CCF-A. [Paper]