Jiangmeng Li (李江梦) Associate Professor, Tenure-Track Science & Technology on Integrated Information System Laboratory Institute of Software, Chinese Academy of Sciences 4#  South  Fourth Street, Zhong Guan Cun Haidian District, Beijing   Email: jiangmeng{at}iscas{dot}ac{dot}cn

Research Interests

My research interests center on Machine Learning, such as Multi-Modal Learning, Self-Supervised Learning, Domain Generalization, Graph Learning, Causal Inference, and etc.

Selected Publications (Full List)

* denotes the co-first author, and | denotes the corresponding author.

• On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation. Wenwen Qiang, Ziyin Gu, Lingyu Si, Jiangmeng Li|, Changwen Zheng, Fuchun Sun, and Hui Xiong. IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI, (2026). [link]
• AmPLe: Supporting Vision-Language Models via Adaptive-Debiased Ensemble Multi-Prompt Learning. Fei Song*, Yi Li*, Jiangmeng Li*|, Rui Wang, Changwen Zheng, Fanjiang Xu, and Hui Xiong. International Journal of Computer Vision, VISI, IJCV, (2026). [link]
• Doubly Debiased Test-Time Prompt Tuning for Vision-Language Models. Fei Song, Yi Li, Rui Wang, Jiahuan Zhou, Changwen Zheng, and Jiangmeng Li|. AAAI 2026, Oral. [link]
• HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning. Qirui Ji, Bin Qin, Yifan Jin, Yunze Zhao, Chuxiong Sun, Changwen Zheng, Jianwen Cao, and Jiangmeng Li|. AAAI 2026. [link]
• M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference. Chuxiong Sun, Peng He, Qirui Ji, Zehua Zang, Jiangmeng Li|, Rui Wang, and Wei Wang. AAAI 2026, Oral. [link]
• TMAE:Learning Targeted Multi-Agent Exploration via Causal Inference. Chuxiong Sun, Dunqi Yao, Rui Wang, Wenwen Qiang, Changwen Zheng, and Jiangmeng Li|. AAAI 2026. [link]
• Benchmarking diffusion models for predicting perturbed cellular responses. Zijun Song, Changwen Zheng, Jiangmeng Li, Linhai Xie, Linhai_Xie，and Yujia Xiang. NeurIPS 2025. [link]
• Knowledge Management Dynamics in a Transformative Environment. Chapter Author: Jiangmeng Li, Fei Song. Book, ISBN 978-1-83634-494-0.
• C2Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning. Kunlun Xu, Yibo Feng, Jiangmeng Li, Yongsheng Qi, and Jiahuan Zhou. NeurIPS 2025. [link]
• Boosting Dynamic Prototyping via Dual-Knowledge Clustering for Semi-Supervised Lifelong Person Re-Identification. Kunlun Xu, Fan Zhuo, Jiangmeng Li, Xu Zou, and Jiahuan Zhou. ICCV 2025. [link]
• CellCLAT: Preserving Topology and Trimming Redundancy in Self-Supervised Cellular Contrastive Learning. Bin Qin*, Qirui Ji*, Jiangmeng Li*|, Yupeng Wang, Xuesong wu|, Jianwen Cao|, and Fanjiang Xu. KDD 2025, Oral. [link]
• Rethinking the Bias of Foundation Model under Long-tailed Distribution. Jiahao Chen*, Bin Qin*, Jiangmeng Li*, Hao Chen, and Bing Su. ICML 2025. [link]
• On the Out-of-Distribution Generalization of Self-Supervised Learning. Wenwen Qiang, Jingyao Wang, Zeen Song, Jiangmeng Li|, and Changwen Zheng. ICML 2025. [link]
• Towards the Causal Complete Cause of Multi-Modal Representation Learning. Jingyao Wang, Siyu Zhao, Wenwen Qiang, Jiangmeng Li, Changwen Zheng, Fuchun Sun, and Hui Xiong. ICML 2025. [link]
• Learning Invariant Causal Mechanism from Vision-Language Models. Zeen Song, Siyu Zhao, Xingyu Zhang, Jiangmeng Li, Changwen Zheng, and Wenwen Qiang. ICML 2025. [link]
• DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training. Yurou Liu, Jiahao Chen, Rui Jiao, Jiangmeng Li, Wenbing Huang, and Bing Su. ICLR 2025. [link]
• Continual Test-Time Adaptation for Single Image Defocus Deblurring via Causal Siamese Networks. Shuang Cui*, Yi Li*, Jiangmeng Li*|, Xiongxin Tang, Bing Su, Fanjiang Xu, and Hui Xiong. International Journal of Computer Vision, VISI, IJCV, (2025). [link]
• Rethinking Generalizability and Discriminability of Self-Supervised Learning from Evolutionary Game Theory Perspective. Jiangmeng Li, Zehua Zang, Qirui Ji, Chuxiong Sun, Wenwen Qiang, Junge Zhang, Changwen Zheng, Fuchun Sun, and Hui Xiong. International Journal of Computer Vision, VISI, IJCV, (2024). [link]
• On the Generalization and Causal Explanation in Self-Supervised Learning. Wenwen Qiang, Zeen Song, Ziyin Gu, Jiangmeng Li|, Changwen Zheng, Fuchun Sun, and Hui Xiong. International Journal of Computer Vision, VISI, IJCV, (2024). [link]
• Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective. Yanan Zhang, Jiangmeng Li*, Lixiang Liu, and Wenwen Qiang. NeurIPS 2024. [link]
• BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction. Jiangmeng Li, Fei Song, Yifan Jin, Wenwen Qiang, Changwen Zheng, Fuchun Sun, and Hui Xiong. ICLR 2024. [link]
• Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning. Jiangmeng Li, Yifan Jin, Hang Gao, Wenwen Qiang, Changwen Zheng, and Fuchun Sun. AAAI 2024. [link]
• Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective. Qirui Ji, Jiangmeng Li*|, Jie Hu, Rui Wang, Changwen Zheng, and Fanjiang Xu. AAAI 2024. [link]
• T2MAC: Targeted and Trusted Multi-Agent Communication Through Selective Engagement and Evidence-Driven Integration. Chuxiong Sun, Zehua Zang, Jiabao Li, Jiangmeng Li|, Xiao Xu, Rui Wang, and Changwen Zheng. AAAI 2024. [link]
• Rethinking Causal Relationships Learning in Graph Neural Networks. Hang Gao, Chengyu Yao, Jiangmeng Li, Lingyu Si, Yifan Jin, Fengge Wu, Changwen Zheng, and Huaping Liu. AAAI 2024. [link]
• Modeling Multiple Views via Implicitly Preserving Global Consistency and Local Complementarity. Jiangmeng Li, Wenwen Qiang, Changwen Zheng, Bing Su, Farid Razzak, Ji-Rong Wen, and Hui Xiong. IEEE Transactions on Knowledge and Data Engineering, Volume 35, 7220-7238 (2023), TKDE. [link]
• Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from a Conditional Causal Perspective. Jiangmeng Li, Yanan Zhang, Wenwen Qiang, Lingyu Si, Chengbo Jiao, Xiaohui Hu, Changwen Zheng, and Fuchun Sun. AAAI 2023. [link]
• Robust Causal Graph Representation Learning against Confounding Effects. Hang Gao*, Jiangmeng Li*|, Wenwen Qiang, Lingyu Si, Bing Xu, Changwen Zheng, and Fuchun Sun. AAAI 2023, Oral. [link]
• Robust Local Preserving and Global Aligning Network for Adversarial Domain Adaptation. Wenwen Qiang*, Jiangmeng Li*, Changwen Zheng, Bing Su, and Hui Xiong. IEEE Transactions on Knowledge and Data Engineering, Volume 35, 3014-3029 (2023), TKDE. [link]
• Meta Attention-Generation Network for Cross-Granularity Few-Shot Learning. Wenwen Qiang*, Jiangmeng Li*, Bing Su, Jianlong Fu, Hui Xiong, and Ji-Rong Wen. International Journal of Computer Vision, Volume 131, 1211-1233 (2023), VISI, IJCV. [link]
• MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning. Jiangmeng Li, Wenwen Qiang, Yanan Zhang, Wenyi Mo, Changwen Zheng, Bing Su, and Hui Xiong. NeurIPS 2022, Spotlight. [link]
• MetAug: Contrastive Learning via Meta Feature Augmentation. Jiangmeng Li, Wenwen Qiang, Changwen Zheng, Bing Su, and Hui Xiong. ICML 2022, Spotlight. [link]
• Interventional Contrastive Learning with Meta Semantic Regularizer. Wenwen Qiang*, Jiangmeng Li*, Changwen Zheng, Bing Su, and Hui Xiong. ICML 2022, Spotlight. [link]
• Bootstrapping Informative Graph Augmentation via A Meta Learning Approach. Hang Gao*, Jiangmeng Li*|, Wenwen Qiang, Lingyu Si, Changwen Zheng, Fuchun Sun. IJCAI 2022. [link]

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