Publications

(* indicates equal contribution)

Conference Papers

1. [NeurIPS'25] SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search.
   Dong Li, Xujiang Zhao, Linlin Yu, Yanchi Liu, Wei Cheng, Zhengzhang Chen, Zhong Chen, Feng Chen, Chen Zhao, Haifeng Chen.
   In Proceedings of the 39th Annual Conference on Neural Information Processing Systems, 2025
2. [ACL'25] Uncertainty Propagation on LLM Agent.
   Qiwei Zhao*, Dong Li*, Yanchi Liu, Wei Cheng, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Huaxiu Yao, Chen Zhao, Haifeng Chen, Xujiang Zhao
   In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, 2025
3. [IJCAI'25] FADE: Towards Fairness-aware Data Generation for Domain Generalization via Classifier-Guided Score-based Diffusion Models.
   Yujie Lin*, Dong Li*, Minglai Shao, Guihong Wan, Chen Zhao
   In Proceedings of the 34th International Joint Conference on Artificial Intelligence, 2025
4. [ICASSP'25] GDDA: Semantic OOD Detection on Graphs under Covariate Shift via Score-Based Diffusion Model.
   Zhixia He, Chen Zhao, Minglai Shao, Yujie Lin, Dong Li, Qin Tian
   In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2025
5. [KDD’25] MLDGG: Meta-Learning for Domain Generalization on Graphs.
   Qin Tian, Chen Zhao, Minglai Shao, Wenjun Wang, Yujie Lin, Dong Li
   In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2025
6. [CIKM’24] Learning Fair Invariant Representations under Covariate and Correlation Shifts Simultaneously.
   Dong Li, Chen Zhao, Minglai Shao, Wenjun Wang.
   In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024.
7. [IJCAI’24] Supervised Algorithmic Fairness in Distribution Shifts: A Survey.
   Minglai Shao*, Dong Li*, Chen Zhao*, Xintao Wu, Yujie Lin, Qin Tian.
   In Proceedings of the 33rd International Joint Conference on Artificial Intelligence, 2024.
8. [CIKM’23] Contrastive Representation Learning Based on Multiple Node-centered Subgraphs.
   Dong Li, Wenjun Wang, Minglai Shao, Chen Zhao.
   In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023.

Journal Papers

1. [DDNS’21] A new early rumor detection model based on bigru neural network.
   Xiangning Chen, Caiyun Wang, Dong Li, Xuemei Sun.
   Discrete Dynamics in Nature and Society, 2021.

Workshop Papers

1. [NeurIPS'25-W] Multi-Modal Foundation Models for Computational Pathology: A Survey.
   Dong Li, Guihong Wan, Xintao Wu, Xinyu Wu, Xiaohui Chen, Yi He, Zhong Chen, Ninghui Hao, Chen Zhao.
   NeurIPS Workshop on Multi-modal Foundation Models and Large Language Models for Life Sciences, 2025
2. [NeurIPS'25-W] A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks.
   Dong Li, Guihong Wan, Xintao Wu, Xinyu Wu, Yi He, Zhong Chen, Ninghui Hao, Chen Zhao.
   NeurIPS Workshop on Imageomics: Discovering Biological Knowledge from Images Using AI, 2025
3. [KDD’25-W] Multi-Modal Out-of-Distribution Detection with Large Language Models.
   Zhixia He, Chen Zhao, Minglai Shao, Dong Li, Qin Tian.
   KDD Workshop on Uncertainty Reasoning and Quantification in Decision Making, 2025.
4. [KDD’25-W] Drift-Aware Proxy Uncertainty Estimation for Large Language Models in Temporal Streams.
   Haoliang Wang, Dong Li, Chen Zhao.
   KDD Workshop on Uncertainty Reasoning and Quantification in Decision Making, 2025.
5. [KDD’24-W] Semantic OOD Detection under Covariate Shift on Graphs with Diffusion Model.
   Zhixia He, Chen Zhao, Minglai Shao, Yujie Lin, Dong Li.
   KDD Workshop on Uncertainty Reasoning and Quantification in Decision Making, 2024.
6. [KDD’24-W] IDGG: Invariant Learning for Out-of-Distribution Generalization on Graphs.
   Qin Tian, Wenjun Wang, Minglai Shao, Chen Zhao, Dong Li.
   KDD Workshop on Uncertainty Reasoning and Quantification in Decision Making, 2024.
7. [KDD’24-W] Fair Data Generation via Score-based Diffusion Model.
   Yujie Lin, Dong Li, Chen Zhao, Minglai Shao.
   KDD Workshop on Ethical Artificial Intelligence: Methods and Applications, 2024.
8. [KDD’23-W] Learning Fair and Domain Generalization Representation.
   Dong Li, Chen Zhao, Minglai Shao, Xujiang Zhao.
   KDD Workshop on Ethical Artificial Intelligence: Methods and Applications, 2023.
9. [IMCEC-W’21] Twitter Rumor Detection Technology Based on Hierarchical Capsule Network.
   Wang Caiyun, Sun Xuemei, Rong Chuitian, Li Dong.
   IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference, 2021.

Preprints

1. Face4FairShifts: A Large Image Benchmark for Fairness and Robust Learning across Visual Domains.
   Yumeng Lin*, Dong Li*, Xintao Wu, Minglai Shao, Xujiang Zhao, Zhong Chen, Chen Zhao. ArXiv preprint, 2509.00658
2. Multi-Modal Foundation Models for Computational Pathology: A Survey.
   Dong Li*, Guihong Wan*, Xintao Wu, Xinyu Wu, Xiaohui Chen, Yi He, Christine G. Lian, Peter K. Sorger, Yevgeniy R. Semenov, Chen Zhao. ArXiv preprint, 2503.09091
3. A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks.
   Dong Li*, Guihong Wan*, Xintao Wu, Xinyu Wu, Ajit J. Nirmal, Christine G. Lian, Peter K. Sorger, Yevgeniy R. Semenov, Chen Zhao.
   ArXiv preprint, 2501.15724
4. Graphs Generalization under Distribution Shifts.
   Qin Tian, Wenjun Wang, Chen Zhao, Minglai Shao, Wang Zhang, Dong Li.
   ArXiv preprint, 2403.16334