Jiangmeng Li (李江梦) 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 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). [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). [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). [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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