| 2026 | ACL | Targeted Exploration via Unified Entropy Control for Reinforcement Learning. | Chen Wang, Lai Wei, Yanzhi Zhang, Chenyang Shao, Zedong Dan, Weiran Huang, Ge Lan, Yue Wang |
| 2025 | ICML | Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization. | Duo Liu, Zhiquan Tan, Linglan Zhao, Zhongqiang Zhang, Xiangzhong Fang, Weiran Huang |
| 2025 | NAACL | FinLLM-B: When Large Language Models Meet Financial Breakout Trading. | Kang Zhang, Osamu Yoshie, Lichao Sun, Weiran Huang |
| 2024 | ECCV | 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 |
| 2024 | ICML | Unveiling the Dynamics of Information Interplay in Supervised Learning. | Kun Song, Zhiquan Tan, Bochao Zou, Huimin Ma, Weiran Huang |
| 2024 | ICML | Information Flow in Self-Supervised Learning. | Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan, Yifan Zhang |
| 2024 | ICML | OTMatch: Improving Semi-Supervised Learning with Optimal Transport. | Zhiquan Tan, Kaipeng Zheng, Weiran Huang |
| 2024 | ICML | Provable Contrastive Continual Learning. | Yichen Wen, Zhiquan Tan, Kaipeng Zheng, Chuanlong Xie, Weiran Huang |
| 2024 | ICML | Matrix Information Theory for Self-Supervised Learning. | Yifan Zhang, Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan |
| 2024 | ICML | A Statistical Theory of Regularization-Based Continual Learning. | Xuyang Zhao, Huiyuan Wang, Weiran Huang, Wei Lin |
| 2023 | ICCV | When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method. | Manyi Zhang, Xuyang Zhao, Jun Yao, Chun Yuan, Weiran Huang |
| 2023 | ICLR | Towards the Generalization of Contrastive Self-Supervised Learning. | Weiran Huang, Mingyang Yi, Xuyang Zhao, Zihao Jiang |
| 2023 | ICLR | Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. | Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang |
| 2023 | ICLR | ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations. | Xuyang Zhao, Tianqi Du, Yisen Wang, Jun Yao, Weiran Huang |
| 2023 | ICML | Rethinking Weak Supervision in Helping Contrastive Learning. | Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang |
| 2022 | AISTATS | Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis. | Jiaye Teng, Weiran Huang, Haowei He |
| 2021 | SIGIR | Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method. | Fuli Feng, Weiran Huang, Xiangnan He, Xin Xin, Qifan Wang, Tat-Seng Chua |
| 2020 | AAAI | Meta-Learning PAC-Bayes Priors in Model Averaging. | Yimin Huang, Weiran Huang, Liang Li, Zhenguo Li |
| 2020 | AAAI | New Interpretations of Normalization Methods in Deep Learning. | Jiacheng Sun, Xiangyong Cao, Hanwen Liang, Weiran Huang, Zewei Chen, Zhenguo Li |
| 2020 | CVPR | Boosting Few-Shot Learning With Adaptive Margin Loss. | Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang |
| 2019 | AAAI | Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks. | Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu |
| 2019 | ICCV | Few-Shot Learning With Global Class Representations. | Aoxue Li, Tiange Luo, Tao Xiang, Weiran Huang, Liwei Wang |
| 2018 | IJCAI | Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications. | Weiran Huang, Jungseul Ok, Liang Li, Wei Chen |
| 2018 | KDD | Multi-Round Influence Maximization. | Lichao Sun, Weiran Huang, Philip S. Yu, Wei Chen |
| 2017 | AAAI | Partitioned Sampling of Public Opinions Based on Their Social Dynamics. | Weiran Huang, Liang Li, Wei Chen |