Publications

*: Equal contribution or alphabetic ordering.
†: Corresponding author.

Conference Papers

NeurIPS ×10, ICML ×9, ICLR ×6, Others ×7

• Enhanced Continual Learning of Vision-Language Models with Model Fusion.
  Haoyuan Gao*, Zicong Zhang*, Yuqi Wei, Linglan Zhao, Guilin Li, Yexin Li, Bo Wang, Linghe Kong, Weiran Huang†.
  International Conference on Learning Representations (ICLR), 2026.
  (Earlier version appeared at ICLR 2025 Workshop on Scalable Optimization for Efficient and Adaptive Foundation Models).

• Idempotent Experience Replay for Reliable Continual Learning.
  Zhanwang Liu*, Yuting Li*, Haoyuan Gao, Yexin Li, Linghe Kong, Lichao Sun, Weiran Huang†.
  International Conference on Learning Representations (ICLR), 2026.

• First SFT, Second RL, Third UPT: Continual Improving Multi-Modal LLM Reasoning via Unsupervised Post-Training.
  Lai Wei, Yuting Li, Chen Wang, Yue Wang, Linghe Kong, Weiran Huang†, Lichao Sun.
  Conference on Neural Information Processing Systems (NeurIPS), 2025.

• PANTHER: Generative Pretraining Beyond Language for Sequential User Behavior Modeling.
  Guilin Li*, Yun Zhang*, Xiuyuan Chen*, Chengqi Li, Bo Wang, Linghe Kong, Wenjia Wang, Weiran Huang†, Matthias Hwai Yong Tan.
  Conference on Neural Information Processing Systems (NeurIPS), 2025.

• Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization.
  Duo Liu, Zhiquan Tan, Linglan Zhao, Zhongqiang Zhang, Xiangzhong Fang, Weiran Huang†.
  International Conference on Machine Learning (ICML), 2025.

• Diabetica: Adapting Large Language Model to Enhance Multiple Medical Tasks in Diabetes Care and Management.
  Lai Wei, Zhen Ying, Muyang He, Yutong Chen, Qian Yang, Yanzhe Hong, jiaping Lu, Kaipeng Zheng, Shaoting Zhang, Xiaoying Li, Weiran Huang†, Ying Chen†.
  ICLR 2025 Workshop on Open Science for Foundation Models (ICLR Workshop), 2025.

• FinLLM-B: When Large Language Models Meet Financial Breakout Trading.
  Kang Zhang, Osamu Yoshie, Lichao Sun, Weiran Huang†.
  Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL) Industry Track, 2025.

• Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models.
  Lai Wei*, Zhiquan Tan*, Chenghai Li, Jindong Wang, Weiran Huang†.
  Conference on Neural Information Processing Systems (NeurIPS), 2024.
  [code] [slides] [知乎]

• SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained Models.
  Linglan Zhao*, Xuerui Zhang*, Ke Yan†, Shouhong Ding, Weiran Huang†.
  Conference on Neural Information Processing Systems (NeurIPS), 2024.

• AutoEval-Video: An Automatic Benchmark for Assessing Large Vision Language Models in Open-Ended Video Question Answering.
  Xiuyuan Chen, Yuan Lin†, Yuchen Zhang†, Weiran Huang†.
  European Conference on Computer Vision (ECCV), 2024.
  [code] [知乎]

• Provable Contrastive Continual Learning.
  Yichen Wen*, Zhiquan Tan*, Kaipeng Zheng, Chuanlong Xie, Weiran Huang†.
  International Conference on Machine Learning (ICML), 2024.
  [知乎]

• OTMatch: Improving Semi-Supervised Learning with Optimal Transport.
  Zhiquan Tan, Kaipeng Zheng, Weiran Huang†.
  International Conference on Machine Learning (ICML), 2024.

• Unveiling the Dynamics of Information Interplay in Supervised Learning.
  Kun Song*, Zhiquan Tan*, Bochao Zou, Huimin Ma†, Weiran Huang†.
  International Conference on Machine Learning (ICML), 2024.
  [知乎]

• A Statistical Theory of Regularization-Based Continual Learning.
  Xuyang Zhao, Huiyuan Wang, Weiran Huang†, Wei Lin†.
  International Conference on Machine Learning (ICML), 2024.

• Information Flow in Self-Supervised Learning.
  Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan, Yifan Zhang.
  International Conference on Machine Learning (ICML), 2024.
  [code]

• Matrix Information Theory for Self-Supervised Learning.
  Yifan Zhang*, Zhiquan Tan*, Jingqin Yang*, Weiran Huang, Yang Yuan.
  International Conference on Machine Learning (ICML), 2024.

• TinyGPT-V: Efficient Multimodal Large Language Model via Small Backbones.
  Zhengqing Yuan, Zhaoxu Li, Weiran Huang, Yanfang Ye, Lichao Sun.
  ICML 2024 Workshop on Advancing Neural Network Training (ICML Workshop), 2024.

• DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation.
  Kaipeng Zheng, Huishuai Zhang, Weiran Huang†.
  Conference on Neural Information Processing Systems (NeurIPS), 2023.
  [code] [知乎]

• FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning.
  Kun Song, Huimin Ma†, Bochao Zou, Huishuai Zhang, Weiran Huang†.
  Conference on Neural Information Processing Systems (NeurIPS), 2023.
  [code] [知乎]

• When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method. (Best Paper Finalist, Top 0.2%)
  Manyi Zhang*, Xuyang Zhao*, Jun Yao, Chun Yuan†, Weiran Huang†.
  International Conference on Computer Vision (ICCV), 2023.

• Rethinking Weak Supervision in Helping Contrastive Representation Learning.
  Jingyi Cui*, Weiran Huang*, Yifei Wang*, Yisen Wang.
  International Conference on Machine Learning (ICML), 2023.

• Towards the Generalization of Contrastive Self-Supervised Learning.
  Weiran Huang*†, Mingyang Yi*, Xuyang Zhao*, Zihao Jiang.
  International Conference on Learning Representations (ICLR), 2023.
  [code] [slides] [知乎]

• ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations.
  Xuyang Zhao*, Tianqi Du*, Yisen Wang, Jun Yao, Weiran Huang†.
  International Conference on Learning Representations (ICLR), 2023.

• Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding.
  Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang†.
  International Conference on Learning Representations (ICLR), 2023.
  [code]

• AggNCE: Asymptotically Identifiable Contrastive Learning. (Oral, Top 5.6%)
  Jingyi Cui*, Weiran Huang*, Yifei Wang, Yisen Wang.
  NeurIPS 2022 Workshop on Self-Supervised Learning Theory and Practice (NeurIPS Workshop), 2022.
  [video]

• Variational Energy-Based Models: A Probabilistic Framework for Contrastive Self-Supervised Learning.
  Tianqi Du*, Yifei Wang*, Weiran Huang, Yisen Wang.
  NeurIPS 2022 Workshop on Self-Supervised Learning Theory and Practice (NeurIPS Workshop), 2022.

• Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis.
  Jiaye Teng*, Weiran Huang*†, Haowei He*.
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2022.
  [slides] [poster] [video] [知乎] [B 站]

• Locally Differentially Private (Contextual) Bandits Learning.
  Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang.
  Conference on Neural Information Processing Systems (NeurIPS), 2020.
  [code] [video] [知乎]

• Boosting Few-Shot Learning with Adaptive Margin Loss.
  Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
  [slides] [patent] [知乎]

• Few-Shot Learning with Global Class Representations.
  Aoxue Li, Tiange Luo, Tao Xiang, Weiran Huang, Liwei Wang.
  International Conference on Computer Vision (ICCV), 2019.
  [code] [poster] [patent] [知乎]

• Community Exploration: From Offline Optimization to Online Learning.
  Xiaowei Chen, Weiran Huang, Wei Chen, John C.S. Lui.
  Conference on Neural Information Processing Systems (NeurIPS), 2018.
  [poster]

• Multi-Round Influence Maximization. (Oral, Top 10.9%)
  Lichao Sun, Weiran Huang, Philip S. Yu, Wei Chen.
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018.
  

Journal Articles

• MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets.
  Lai Wei, Xiaozhe Li, Zihao Jiang, Weiran Huang†, Lichao Sun.
  Artificial Intelligence for Engineering, 2025.
  [200 selected data] [机器之心]

• RhythmFormer: Extracting Patterned rPPG Signals based on Periodic Sparse Attention.
  Bochao Zou, Zizheng Guo, Jiansheng Chen, Junbao Zhuo, Weiran Huang, Huimin Ma.
  Pattern Recognition, 2025.

• Tree-Based Ensemble Machine Learning Models in the Prediction of Acute Respiratory Distress Syndrome Following Cardiac Surgery: A Multicenter Cohort Study.
  Hang Zhang, Dewei Qian, Xiaomiao Zhang, Peize Meng, Weiran Huang, Tongtong Gu, Yongliang Fan, Yi Zhang, Yuchen Wang, Min Yu, Zhongxiang Yuan, Xin Chen, Qingnan Zhao, Zheng Ruan.
  Journal of Translational Medicine 22, 772, 2024.