ICML Little By Little: Continual Learning via Incremental Mixture of Rank-1 Associative Memory Experts Haodong Lu, Chongyang Zhao, Minhui Xue, Lina Yao, Kristen Moore, Dong Gong International Conference on Machine Learning (ICML), 2026 OpenReview ARXIV Project Github CVPR On Token’s Dilemma: Dynamic MoE with Drift-Aware Token Assignment for Continual Learning of Large Vision Language Models Chongyang Zhao, Mingsong Li, Haodong Lu, Dong Gong Computer Vision and Pattern Recognition Conference (CVPR), 2026 ARXIV Project Github Preprint Adaptive Rank, Reduced Forgetting: Knowledge Retention in Continual Learning Vision-Language Models with Dynamic Rank-Selective LoRA Haodong Lu, Chongyang Zhao, Minhui Xue, Lina Yao, Kristen Moore, Dong Gong Preprint. Under Review ARXIV Github ICLR Learning with Mixture of Prototypes for Out-of-Distribution Detection Haodong Lu, Dong Gong, Shuo Wang, Minhui Xue, Lina Yao, Kristen Moore In the 12th International Conference on Learning Representations (ICLR), 2024. ICLR Github CVPR Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning Huiyi Wang, Haodong Lu, Lina Yao, Dong Gong Computer Vision and Pattern Recognition Conference (CVPR), 2025 CVPR Github TMLR Continual Learning on CLIP via Incremental Prompt Tuning with Intrinsic Textual Anchor Haodong Lu, Xinyu Zhang, Kristen Moore, Minhui Xue, Lina Yao, Anton van den Hengel, Dong Gong Transactions on Machine Learning Research (TMLR), 2025 TMLR Github NeurIPS Model Inversion with Layer-Specific Modeling and Alignment for Data-Free Continual Learning Rui Tong, Haodong Lu, Yuxuan Liu, Dong Gong Advances in Neural Information Processing Systems (NeurIPS), 2025 NeurIPS Github WWW Balancing Plasticity and Stability via Dual-Branch Learning in Online Continual Learning Xu Han, Haodong Lu, Huiyi Wang, Dong Gong The ACM Web Conference (WWW) - short paper track, 2025 WWW Github