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

Vision-Language Model Selection and Reuse for Downstream Adaptation.
Hao-Zhe Tan, Zhi Zhou, Yu-Feng Li, Lan-Zhe Guo.
In: Proceedings of the 42nd International Conference on Machine Learning, Vancouver, 2025.
ICML 2025, CCF-A
Paper / Code

Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible.
Lin-Han Jia, Wen-Chao Hu, Jie-Jing Shao, Lan-Zhe Guo, Yu-Feng Li.
In: Proceedings of the 42nd International Conference on Machine Learning, Vancouver, 2025.
ICML 2025, CCF-A
Paper

D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning.
Jia Zhang, Chen-Xi Zhang, Yao Liu, Yi-Xuan Jin, Xiao-Wen Yang, Bo Zheng, Yi Liu, Lan-Zhe Guo.
In: Proceedings of the 34th International Joint Conference on Artificial Intelligence, Montreal, 2025.
IJCAI 2025, CCF-A
Paper

LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model.
Zhi Zhou, Jiang-Xin Shi, Peng-Xiao Song, Xiao-Wen Yang, Yi-Xuan Jin, Lan-Zhe Guo, Yu-Feng Li.
In: Proceedings of the 1st SCI-FM Workshop in ICLR 2025, Singapore, 2025.
SCI-FM Workshop @ ICLR 2025
Paper / Code/ Project Page

Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model.
Rundong He, Yicong Dong, Lan-Zhe Guo, Yilong Yin, Tailin Wu.
In: Proceedings of the 13th International Conference on Learning Representations, Singapore, 2025.
ICLR 2025, CAAI-A
Paper / Code

Fully Test-time Adaptation for Tabular Data.
Zhi Zhou, Yu-Kun Yang, Lan-Zhe Guo^✉, Yu-Feng Li^✉.
In: Proceedings of the 39th AAAI conference on Artificial Intelligence, Philadelphia, 2025. Page: 23027-23035.
AAAI 2025, CCF-A
Paper / Code

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 41st International Conference on Machine Learning, Vienna, 2024. Page: 62161-62177.
ICML 2024, CCF-A
Paper / Code / Project Page

Offline Imitation Learning with Model-based Reverse Augmentation.
Jie-Jing Shao, Hao-Sen Shi, Lan-Zhe Guo^✉, Yu-Feng Li^✉.
In: Proceedings of the 30th SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, 2024. Page: 2608-2617.
KDD 2024, CCF-A
Paper / Code / Project Page

Realistic Evaluation of Semi-Supervised Learning Algorithms in Open Environments.
Lin-Han Jia, Lan-Zhe Guo^✉, Yu-Feng Li^✉.
In: Proceedings of the 12th International Conference on Learning Representations, Vienna, 2024.
ICLR 2024, CAAI-A
Paper / Code / Project Page

You Only Submit One Image to Find the Most Suitable Generative Model.
Zhi Zhou, Lan-Zhe Guo, Peng-Xiao Song, Yu-Feng Li.
In: NeurIPS Workshop On Diffusion, New Orleans, 2023.
Diffusion Workshop @ NeurIPS 2023
Paper

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

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
Paper / Code

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
Paper / Code

DualMatch: Robust Semi-Supervised Learning with Dual-Level Interaction.
Cong Wang, Xiao-Feng Cao, Lan-Zhe Guo, Zeng-Lin Shi.
In: Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, Turin, Italy, 2023. Page: 102--119.
ECML/PKDD 2023
Paper / Code

Robust Semi-Supervised Learning when Not All Classes have Labels.
Lan-Zhe Guo, Yi-Ge Zhang, Zhi-Fan Wu, Jie-Jing Shao, Yu-Feng Li.
In: Advances in Neural Information Processing Systems, New Orleans, LA, 2022. Page: 3305-3317.
NeurIPS 2022, CCF-A
Paper / Code

LOG: Active Model Adaptation for Label-Efficient OOD Generalization.
Jie-Jing Shao, Lan-Zhe Guo, Xiao-Wen Yang, Yu-Feng Li.
In: Advances in Neural Information Processing Systems, New Orleans, LA, 2022. Page: 11023-11034.
NeurIPS 2022, CCF-A
Paper / Code

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 / Project Page

Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding.
Lan-Zhe Guo, Yu-Feng Li.
In: Proceedings of the 39th International Conference on Machine Learning, Baltimore, Maryland, 2022. Page: 8082-8094.
ICML 2022, CCF-A
Paper / Code

STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data.
Zhi Zhou, Lan-Zhe Guo (co-first author), Zhan-Zhan Cheng, Yu-Feng Li, Shi-Liang Pu.
In: Advances in Neural Information Processing Systems, Virtual Conference, 2021. Page: 29168-29180.
ICML 2021, CCF-A
Paper / Code / Poster

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

Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data.
Lan-Zhe Guo, Zhen-Yu Zhang, Yuan Jiang, Yu-Feng Li, Zhi-Hua Zhou.
In: Proceedings of the 37th International Conference on Machine Learning, Vienna, Austria, 2020. Page: 3897-3906.
ICML 2020, CCF-A
Paper / Code

RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift.
Lan-Zhe Guo, Zhi Zhou, 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

Weakly Supervised Learning Meets Ride-Sharing User Experience Enhancement.
Lan-Zhe Guo, Feng Kuang, Zhang-Xun Liu, Yu-Feng Li, Nan Ma, Xiao-Hu Qie.
In: Proceedings of the 34rd AAAI conference on Artificial Intelligence, New York, NY, 2020. Page: 4052-4059.
AAAI 2020, CCF-A
Paper

Robust Semi-Supervised Representation Learning for Graph-Structublue Data.
Lan-Zhe Guo, Tao Han, Yu-Feng Li.
In: Proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, Macau, China. 2019. Page: 131--143.
PAKDD 2019
Paper

A General Formulation for Safely Exploiting Weakly Supervised Data.
Lan-Zhe Guo, Yu-Feng Li.
In: Proceedings of the 32nd AAAI conference on Artificial Intelligence, New Orleans, LA, 2018. Page: 3126-3133.
AAAI 2018, CCF-A
Paper

Large Margin Graph Construction for Semi-Supervised Learning.
Lan-Zhe Guo, Shao-Bo Wang, Yu-Feng Li.
In: 2018 IEEE International Conference on Data Mining Workshops, Singapore, 2018. Page: 1030-1033.
Graph Learning Workshop @ ICDM 2018
Paper

Robust Semi-Supervised Learning in Open Environments.
Lan-Zhe Guo, Lin-Han Jia, Jie-Jing Shao, Yu-Feng Li.
Frontiers o of Computer Science, 2025.
FCS 2025, CCF-B
Paper

Interactive Reweighting for Mitigating Label Quality Issues.
Wei-Kai Yang, Yu-Kai Guo, Jing Wu, Zheng Wang, Lan-Zhe Guo, Yu-Feng Li, Shixia Liu.
IEEE Transactions on Visualization and Computer Graphics, 30(3):1837-1852, 2024.
TVCG 2024, CCF-A
Paper

LAMDA-SSL: A Comprehensive Semi-Supervised Learning Toolkit.
Lin-Han Jia, Lan-Zhe Guo^✉, Zhi Zhou, Yu-Feng Li^✉.
SCIENCE CHINA Information Sciences, 67:117101, 2024.
SCIS 2024, CCF-B
Paper / Code / Project Page

稳健选择伪标注的混合式半监督学习.
Lan-Zhe Guo, Yu-Feng Li.
中国科学：信息科学, 54(3):623–637, 2024.
中国科学：信息科学 2024, CCF-A类中文期刊
Paper

Open-Set Learning under Covariate Shift.
Jie-Jing Shao, Xiao-Wen Wang, Lan-Zhe Guo^✉.
Machine Learning, 113(4):1643-1659, 2024.
MLJ 2024, CCF-B
Paper

Transfer and Share: Semi-Supervised Learning from Long-Tailed Data.
Tong-Wei, Qian-Yu Liu, Jiang-Xin Shi, Wei-Wei Tu, Lan-Zhe Guo^✉.
Machine Learning, 113(4):1725-1742, 2024.
MLJ 2024, CCF-B
Paper / Code

Towards Safe Weakly Supervised Learning.
Yu-Feng Li, Lan-Zhe Guo (co-first author), Zhi-Hua Zhou.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(1): 334-346, 2021.
IEEE TPAMI 2021, CCF-A, 入选2024年江苏省自然科学百篇优秀学术论文
Paper

Interactive Graph Construction for Graph-Based Semi-Supervised Learning.
Chang-Jian Chen, Zhao-Wei Wang, Jing Wu, Xi-Ting Wang, Lan-Zhe Guo, Yu-Feng Li, Shi-Xia Liu.
IEEE Transactions on Visualization and Computer Graphics (TVCG), 27(9): 3701-3716, 2021.
IEEE TVCG 2021, CCF-A
Paper

Learning From Group Supervision: The Impact of Supervision Deficiency on Multi-Label Learning.
Miao Xu, Lan-Zhe Guo^✉.
Science China Information Science, 64(3): 1-13, 2021.
SCIS 2021, CCF-B
Paper

Learning Safe Multi-Label Pblueiction for Weakly Labeled Data.
Tong Wei, Lan-Zhe Guo, Yu-Feng Li, Wei Gao.
Machine Learning, 107(4): 703-725, 2018.
MLJ 2021, CCF-B
Paper