Han, Bo

204 publications

ICML 2025 A Lens into Interpretable Transformer Mistakes via Semantic Dependency Ruo-Jing Dong, Yu Yao, Bo Han, Tongliang Liu

ICLR 2025 A Robust Method to Discover Causal or Anticausal Relation Yu Yao, Yang Zhou, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu

ICML 2025 Adaptive Localization of Knowledge Negation for Continual LLM Unlearning Abudukelimu Wuerkaixi, Qizhou Wang, Sen Cui, Wutong Xu, Bo Han, Gang Niu, Masashi Sugiyama, Changshui Zhang

NeurIPS 2025 Advancing Machine-Generated Text Detection from an Easy to Hard Supervision Perspective Chenwang Wu, Yiu-ming Cheung, Bo Han, Defu Lian

MLJ 2025 Alignclip: Navigating the Misalignments for Robust Vision-Language Generalization Zhongyi Han, Gongxu Luo, Hao Sun, Yaqian Li, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu

ICLR 2025 Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation Yikun Zhang, Geyan Ye, Chaohao Yuan, Bo Han, Long-Kai Huang, Jianhua Yao, Wei Liu, Yu Rong

ICML 2025 COSDA: Counterfactual-Based Susceptibility Risk Framework for Open-Set Domain Adaptation Wenxu Wang, Rui Zhou, Jing Wang, Yun Zhou, Cheng Zhu, Ruichun Tang, Bo Han, Nevin L. Zhang

NeurIPS 2025 Detecting Generated Images by Fitting Natural Image Distributions Yonggang Zhang, Jun Nie, Xinmei Tian, Mingming Gong, Kun Zhang, Bo Han

AAAI 2025 Eliciting Causal Abilities in Large Language Models for Reasoning Tasks Yajing Wang, Zongwei Luo, Jingzhe Wang, Zhanke Zhou, Yongqiang Chen, Bo Han

NeurIPS 2025 Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples Suqin Yuan, Lei Feng, Bo Han, Tongliang Liu

NeurIPS 2025 Epistemic Uncertainty for Generated Image Detection Jun Nie, Yonggang Zhang, Tongliang Liu, Yiu-ming Cheung, Bo Han, Xinmei Tian

ICML 2025 Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning Puning Yang, Qizhou Wang, Zhuo Huang, Tongliang Liu, Chengqi Zhang, Bo Han

ICLR 2025 Fast and Accurate Blind Flexible Docking Zizhuo Zhang, Lijun Wu, Kaiyuan Gao, Jiangchao Yao, Tao Qin, Bo Han

NeurIPS 2025 FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning Zhiqin Yang, Yonggang Zhang, Chenxin Li, Yiu-ming Cheung, Bo Han, Yixuan Yuan

TMLR 2025 Federated Generalized Novel Category Discovery with Prompts Tuning Lei Shen, Nan Pu, Zhun Zhong, Mingming Gong, Dianhai Yu, Chengqi Zhang, Bo Han

ICML 2025 From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium Xie Yi, Zhanke Zhou, Chentao Cao, Qiyu Niu, Tongliang Liu, Bo Han

ICML 2025 From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions Under Incomplete Information? Zhanke Zhou, Xiao Feng, Zhaocheng Zhu, Jiangchao Yao, Sanmi Koyejo, Bo Han

ICML 2025 GRU: Mitigating the Trade-Off Between Unlearning and Retention for LLMs Yue Wang, Qizhou Wang, Feng Liu, Wei Huang, Yali Du, Xiaojiang Du, Bo Han

NeurIPS 2025 Generative Model Inversion Through the Lens of the Manifold Hypothesis Xiong Peng, Bo Han, Fengfei Yu, Tongliang Liu, Feng Liu, Mingyuan Zhou

ICCV 2025 Golden Noise for Diffusion Models: A Learning Framework Zikai Zhou, Shitong Shao, Lichen Bai, Shufei Zhang, Zhiqiang Xu, Bo Han, Zeke Xie

ICLR 2025 Hot-Pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection Lei Shen, Zhenheng Tang, Lijun Wu, Yonggang Zhang, Xiaowen Chu, Tao Qin, Bo Han

ICLR 2025 Instance-Dependent Early Stopping Suqin Yuan, Runqi Lin, Lei Feng, Bo Han, Tongliang Liu

NeurIPS 2025 Keep It on a Leash: Controllable Pseudo-Label Generation Towards Realistic Long-Tailed Semi-Supervised Learning Yaxin Hou, Bo Han, Yuheng Jia, Hui Liu, Junhui Hou

ICLRW 2025 Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models Zhanke Zhou, Xuan Li, Zhaocheng Zhu, Mikhail Galkin, Xiao Feng, Sanmi Koyejo, Jian Tang, Bo Han

ICML 2025 Learning Without Isolation: Pathway Protection for Continual Learning Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui, Haoxuan Li, Ding Li, Jingfeng Zhang, Bo Han, Gang Niu, Houfang Liu, Yi Yang, Sifan Yang, Changshui Zhang, Tianling Ren

NeurIPS 2025 Learning to Instruct for Visual Instruction Tuning Zhihan Zhou, Feng Hong, Jiaan Luo, Yushi Ye, Jiangchao Yao, Dongsheng Li, Bo Han, Ya Zhang, Yanfeng Wang

ICLR 2025 Noisy Test-Time Adaptation in Vision-Language Models Chentao Cao, Zhun Zhong, Zhanke Zhou, Tongliang Liu, Yang Liu, Kun Zhang, Bo Han

ICLRW 2025 On the Language of Thoughts in Large Language Models Chenxi Liu, Yongqiang Chen, Tongliang Liu, James Cheng, Bo Han, Kun Zhang

IJCAI 2025 One-Shot Federated Learning Methods: A Practical Guide Xiang Liu, Zhenheng Tang, Xia Li, Yijun Song, Sijie Ji, Zemin Liu, Bo Han, Linshan Jiang, Jialin Li

NeurIPS 2025 Physics-Driven Spatiotemporal Modeling for AI-Generated Video Detection Shuhai Zhang, ZiHao Lian, Jiahao Yang, Daiyuan Li, Guoxuan Pang, Feng Liu, Bo Han, Shutao Li, Mingkui Tan

NeurIPS 2025 Practical Kernel Selection for Kernel-Based Conditional Independence Test Wenjie Wang, Mingming Gong, Biwei Huang, James Bailey, Bo Han, Kun Zhang, Feng Liu

AAAI 2025 Provable Discriminative Hyperspherical Embedding for Out-of-Distribution Detection Zhipeng Zou, Sheng Wan, Guangyu Li, Bo Han, Tongliang Liu, Lin Zhao, Chen Gong

ICLR 2025 Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q Weinberger

ICLR 2025 Towards Effective Evaluations and Comparisons for LLM Unlearning Methods Qizhou Wang, Bo Han, Puning Yang, Jianing Zhu, Tongliang Liu, Masashi Sugiyama

ICLR 2025 Towards Out-of-Modal Generalization Without Instance-Level Modal Correspondence Zhuo Huang, Gang Niu, Bo Han, Masashi Sugiyama, Tongliang Liu

IJCAI 2025 Towards Regularized Mixture of Predictions for Class-Imbalanced Semi-Supervised Facial Expression Recognition Hangyu Li, Yixin Zhang, Jiangchao Yao, Nannan Wang, Bo Han

ICLR 2025 Understanding and Enhancing the Transferability of Jailbreaking Attacks Runqi Lin, Bo Han, Fengwang Li, Tongliang Liu

NeurIPS 2025 Unlocker: Disentangle the Deadlock of Learning Between Label-Noisy and Long-Tailed Data Chen Shu, HongJun Xu, Ruichi Zhang, Mengke Li, Yonggang Zhang, Yang Lu, Bo Han, Yiu-ming Cheung, Hanzi Wang

ICML 2025 When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap Is All You Need Ziming Hong, Runnan Chen, Zengmao Wang, Bo Han, Bo Du, Tongliang Liu

NeurIPS 2024 A Sober Look at the Robustness of CLIPs to Spurious Features Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang

AAAI 2024 AMD: Autoregressive Motion Diffusion Bo Han, Hao Peng, Minjing Dong, Yi Ren, Yixuan Shen, Chang Xu

ICLR 2024 Accurate Forgetting for Heterogeneous Federated Continual Learning Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang, Kunda Yan, Bo Han, Gang Niu, Lei Fang, Changshui Zhang, Masashi Sugiyama

ICML 2024 Balancing Similarity and Complementarity for Federated Learning Kunda Yan, Sen Cui, Abudukelimu Wuerkaixi, Jingfeng Zhang, Bo Han, Gang Niu, Masashi Sugiyama, Changshui Zhang

NeurIPS 2024 Can Language Models Perform Robust Reasoning in Chain-of-Thought Prompting with Noisy Rationales? Zhanke Zhou, Rong Tao, Jianing Zhu, Yiwen Luo, Zengmao Wang, Bo Han

ICLRW 2024 Can Large Language Models Reason Robustly with Noisy Rationales? Zhanke Zhou, Rong Tao, Jianing Zhu, Yiwen Luo, Zengmao Wang, Bo Han

NeurIPSW 2024 DeepInception: Hypnotize Large Language Model to Be Jailbreaker Xuan Li, Zhanke Zhou, Jianing Zhu, Jiangchao Yao, Tongliang Liu, Bo Han

ICLR 2024 Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy Shuhai Zhang, Yiliao Song, Jiahao Yang, Yuanqing Li, Bo Han, Mingkui Tan

NeurIPS 2024 Discovery of the Hidden World with Large Language Models Chenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang

MLJ 2024 Efficient Private SCO for Heavy-Tailed Data via Averaged Clipping Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Tieyong Zeng

ICLR 2024 Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation Jiyang Zheng, Yu Yao, Bo Han, Dadong Wang, Tongliang Liu

AAAI 2024 Enhancing Evolving Domain Generalization Through Dynamic Latent Representations Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng

ICLR 2024 Enhancing Neural Subset Selection: Integrating Background Information into Set Representations Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng

ICLR 2024 Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting Rong Dai, Yonggang Zhang, Ang Li, Tongliang Liu, Xun Yang, Bo Han

ICML 2024 Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han

TMLR 2024 Exploit CAM by Itself: Complementary Learning System for Weakly Supervised Semantic Segmentation Wankou Yang, Jiren Mai, Fei Zhang, Tongliang Liu, Bo Han

MLJ 2024 Exploiting Counter-Examples for Active Learning with Partial Labels Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, Bo Han

ICLR 2024 FedImpro: Measuring and Improving Client Update in Federated Learning Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xinmei Tian, Tongliang Liu, Bo Han, Xiaowen Chu

AAAI 2024 Federated Learning with Extremely Noisy Clients via Negative Distillation Yang Lu, Lin Chen, Yonggang Zhang, Yiliang Zhang, Bo Han, Yiu-ming Cheung, Hanzi Wang

NeurIPS 2024 Few-Shot Adversarial Prompt Learning on Vision-Language Models Yiwei Zhou, Xiaobo Xia, Zhiwei Lin, Bo Han, Tongliang Liu

NeurIPS 2024 FuseFL: One-Shot Federated Learning Through the Lens of Causality with Progressive Model Fusion Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu-ming Cheung, Amelie Chi Zhou, Bo Han, Xiaowen Chu

TMLR 2024 HiFE: Hierarchical Feature Ensemble Framework for Few-Shot Hypotheses Adaptation Yongfeng Zhong, Haoang Chi, Feng Liu, Xiao-Ming Wu, Bo Han

NeurIPSW 2024 Hot Pluggable Federated Learning Lei Shen, Zhenheng Tang, Lijun Wu, Yonggang Zhang, Xiaowen Chu, Tao Qin, Bo Han

ICML 2024 How Interpretable Are Interpretable Graph Neural Networks? Yongqiang Chen, Yatao Bian, Bo Han, James Cheng

ICLRW 2024 Interpretable and Generalizable Graph Learning via Subgraph Multilinear Extension Yongqiang Chen, Yatao Bian, Bo Han, James Cheng

ICML 2024 Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency Runqi Lin, Chaojian Yu, Bo Han, Hang Su, Tongliang Liu

ICLR 2024 Less Is More: One-Shot Subgraph Reasoning on Large-Scale Knowledge Graphs Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han

IJCAI 2024 MCM: Multi-Condition Motion Synthesis Framework Zeyu Ling, Bo Han, Yongkang Wong, Han Lin, Mohan S. Kankanhalli, Weidong Geng

ICML 2024 MOKD: Cross-Domain Finetuning for Few-Shot Classification via Maximizing Optimized Kernel Dependence Hongduan Tian, Feng Liu, Tongliang Liu, Bo Du, Yiu-Ming Cheung, Bo Han

NeurIPS 2024 Mind the Gap Between Prototypes and Images in Cross-Domain Finetuning Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han

ICML 2024 Mitigating Label Noise on Graphs via Topological Sample Selection Yuhao Wu, Jiangchao Yao, Xiaobo Xia, Jun Yu, Ruxin Wang, Bo Han, Tongliang Liu

CVPR 2024 Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning Zihua Zhao, Mengxi Chen, Tianjie Dai, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang

ICLR 2024 Negative Label Guided OOD Detection with Pretrained Vision-Language Models Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han

ICLR 2024 Neural Atoms: Propagating Long-Range Interaction in Molecular Graphs Through Efficient Communication Channel Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han

ICLR 2024 NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models Beyond Spherical Linear Interpolation PengFei Zheng, Yonggang Zhang, Zhen Fang, Tongliang Liu, Defu Lian, Bo Han

JMLR 2024 On the Learnability of Out-of-Distribution Detection Zhen Fang, Yixuan Li, Feng Liu, Bo Han, Jie Lu

ICLR 2024 On the Over-Memorization During Natural, Robust and Catastrophic Overfitting Runqi Lin, Chaojian Yu, Bo Han, Tongliang Liu

MLJ 2024 Online Binary Classification from Similar and Dissimilar Data Senlin Shu, Haobo Wang, Zhuowei Wang, Bo Han, Tao Xiang, Bo An, Lei Feng

ICLR 2024 Out-of-Distribution Detection with Negative Prompts Jun Nie, Yonggang Zhang, Zhen Fang, Tongliang Liu, Bo Han, Xinmei Tian

IJCAI 2024 ParsNets: A Parsimonious Composition of Orthogonal and Low-Rank Linear Networks for Zero-Shot Learning Jingcai Guo, Qihua Zhou, Xiaocheng Lu, Ruibin Li, Ziming Liu, Jie Zhang, Bo Han, Junyang Chen, Xin Xie, Song Guo

NeurIPS 2024 Pseudo-Private Data Guided Model Inversion Attacks Xiong Peng, Bo Han, Feng Liu, Tongliang Liu, Mingyuan Zhou

NeurIPS 2024 Revive Re-Weighting in Imbalanced Learning by Density Ratio Estimation Jiaan Luo, Feng Hong, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang

ICLR 2024 Robust Training of Federated Models with Extremely Label Deficiency Yonggang Zhang, Zhiqin Yang, Xinmei Tian, Nannan Wang, Tongliang Liu, Bo Han

NeurIPS 2024 Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection Geng Yu, Jianing Zhu, Jiangchao Yao, Bo Han

ICML 2024 Towards Realistic Model Selection for Semi-Supervised Learning Muyang Li, Xiaobo Xia, Runze Wu, Fengming Huang, Jun Yu, Bo Han, Tongliang Liu

IJCAI 2024 Trustworthy Machine Learning Under Imperfect Data Bo Han

JAIR 2024 USN: A Robust Imitation Learning Method Against Diverse Action Noise Xingrui Yu, Bo Han, Ivor W. Tsang

TMLR 2024 Understanding Fairness Surrogate Functions in Algorithmic Fairness Wei Yao, Zhanke Zhou, Zhicong Li, Bo Han, Yong Liu

ICML 2024 Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning Yuhao Wu, Jiangchao Yao, Bo Han, Lina Yao, Tongliang Liu

NeurIPS 2024 Unveiling Causal Reasoning in Large Language Models: Reality or Mirage? Haoang Chi, He Li, Wenjing Yang, Feng Liu, Long Lan, Xiaoguang Ren, Tongliang Liu, Bo Han

NeurIPS 2024 What if the Input Is Expanded in OOD Detection? Boxuan Zhang, Jianing Zhu, Zengmao Wang, Tongliang Liu, Bo Du, Bo Han

ICLR 2023 A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond Lin Yong, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao, Xiao Zhou, Tongliang Liu, Bo Han

ICML 2023 A Universal Unbiased Method for Classification from Aggregate Observations Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen

CVPR 2023 Adjustment and Alignment for Unbiased Open Set Domain Adaptation Wuyang Li, Jie Liu, Bo Han, Yixuan Yuan

NeurIPS 2023 Combating Bilateral Edge Noise for Robust Link Prediction Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, Li He, Liang Wang, Bo Zheng, Bo Han

ICLR 2023 Combating Exacerbated Heterogeneity for Robust Models in Federated Learning Jianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han

ICCV 2023 Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples Xiaobo Xia, Bo Han, Yibing Zhan, Jun Yu, Mingming Gong, Chen Gong, Tongliang Liu

NeurIPS 2023 Combating Representation Learning Disparity with Geometric Harmonization Zhihan Zhou, Jiangchao Yao, Feng Hong, Ya Zhang, Bo Han, Yanfeng Wang

ICML 2023 Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score Shuhai Zhang, Feng Liu, Jiahao Yang, Yifan Yang, Changsheng Li, Bo Han, Mingkui Tan

ICML 2023 Detecting Out-of-Distribution Data Through In-Distribution Class Prior Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han

NeurIPS 2023 Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation Jianing Zhu, Yu Geng, Jiangchao Yao, Tongliang Liu, Gang Niu, Masashi Sugiyama, Bo Han

ICML 2023 Diversity-Enhancing Generative Network for Few-Shot Hypothesis Adaptation Ruijiang Dong, Feng Liu, Haoang Chi, Tongliang Liu, Mingming Gong, Gang Niu, Masashi Sugiyama, Bo Han

NeurIPS 2023 Does Invariant Graph Learning via Environment Augmentation Learn Invariance? Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng

ICML 2023 Exploring Model Dynamics for Accumulative Poisoning Discovery Jianing Zhu, Xiawei Guo, Jiangchao Yao, Chao Du, Li He, Shuo Yuan, Tongliang Liu, Liang Wang, Bo Han

NeurIPS 2023 FedFed: Feature Distillation Against Data Heterogeneity in Federated Learning Zhiqin Yang, Yonggang Zhang, Yu Zheng, Xinmei Tian, Hao Peng, Tongliang Liu, Bo Han

NeurIPS 2023 Federated Learning with Bilateral Curation for Partially Class-Disjoint Data Ziqing Fan, Ruipeng Zhang, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang

NeurIPS 2023 FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning Zhuo Huang, Li Shen, Jun Yu, Bo Han, Tongliang Liu

CVPR 2023 Hard Sample Matters a Lot in Zero-Shot Quantization Huantong Li, Xiangmiao Wu, Fanbing Lv, Daihai Liao, Thomas H. Li, Yonggang Zhang, Bo Han, Mingkui Tan

ICLR 2023 Harnessing Out-of-Distribution Examples via Augmenting Content and Style Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu

ICCV 2023 Holistic Label Correction for Noisy Multi-Label Classification Xiaobo Xia, Jiankang Deng, Wei Bao, Yuxuan Du, Bo Han, Shiguang Shan, Tongliang Liu

NeurIPS 2023 InstanT: Semi-Supervised Learning with Instance-Dependent Thresholds Muyang Li, Runze Wu, Haoyu Liu, Jun Yu, Xun Yang, Bo Han, Tongliang Liu

TMLR 2023 KRADA: Known-Region-Aware Domain Alignment for Open-Set Domain Adaptation in Semantic Segmentation Chenhong Zhou, Feng Liu, Chen Gong, Rongfei Zeng, Tongliang Liu, William Cheung, Bo Han

ICCV 2023 Label-Noise Learning with Intrinsically Long-Tailed Data Yang Lu, Yiliang Zhang, Bo Han, Yiu-ming Cheung, Hanzi Wang

NeurIPS 2023 Learning to Augment Distributions for Out-of-Distribution Detection Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han

NeurIPSW 2023 Long-Range Neural Atom Learning for Molecular Graphs Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han

ICLR 2023 Moderate Coreset: A Universal Method of Data Selection for Real-World Data-Efficient Deep Learning Xiaobo Xia, Jiale Liu, Jun Yu, Xu Shen, Bo Han, Tongliang Liu

ICML 2023 Moderately Distributional Exploration for Domain Generalization Rui Dai, Yonggang Zhang, Zhen Fang, Bo Han, Xinmei Tian

AAAI 2023 NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension Xin He, Jiangchao Yao, Yuxin Wang, Zhenheng Tang, Ka Chun Cheung, Simon See, Bo Han, Xiaowen Chu

TMLR 2023 Noise-Robust Graph Learning by Estimating and Leveraging Pairwise Interactions Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Yixuan Li, Junzhou Huang

ICML 2023 On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han

NeurIPS 2023 Out-of-Distribution Detection Learning with Unreliable Out-of-Distribution Sources Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han

ICLR 2023 Out-of-Distribution Detection with Implicit Outlier Transformation Qizhou Wang, Junjie Ye, Feng Liu, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han

ICLR 2023 Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Ma Kaili, Han Yang, Peilin Zhao, Bo Han, James Cheng

ICCV 2023 Partition Speeds up Learning Implicit Neural Representations Based on Exponential-Increase Hypothesis Ke Liu, Feng Liu, Haishuai Wang, Ning Ma, Jiajun Bu, Bo Han

CVPR 2023 Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu

NeurIPS 2023 SODA: Robust Training of Test-Time Data Adaptors Zige Wang, Yonggang Zhang, Zhen Fang, Long Lan, Wenjing Yang, Bo Han

NeurIPS 2023 Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping Yingbin Bai, Zhongyi Han, Erkun Yang, Jun Yu, Bo Han, Dadong Wang, Tongliang Liu

NeurIPSW 2023 Towards Out-of-Distribution Generalizable Predictions of Chemical Kinetic Properties Zihao Wang, Yongqiang Chen, Yang Duan, Weijiang Li, Bo Han, James Cheng, Hanghang Tong

NeurIPS 2023 Understanding and Improving Feature Learning for Out-of-Distribution Generalization Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng

ICML 2023 Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability Jianing Zhu, Hengzhuang Li, Jiangchao Yao, Tongliang Liu, Jianliang Xu, Bo Han

ICML 2023 Which Is Better for Learning with Noisy Labels: The Semi-Supervised Method or Modeling Label Noise? Yu Yao, Mingming Gong, Yuxuan Du, Jun Yu, Bo Han, Kun Zhang, Tongliang Liu

ICLR 2022 Adversarial Robustness Through the Lens of Causality Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang

NeurIPS 2022 Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks Jianan Zhou, Jianing Zhu, Jingfeng Zhang, Tongliang Liu, Gang Niu, Bo Han, Masashi Sugiyama

NeurIPS 2022 Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization De Cheng, Yixiong Ning, Nannan Wang, Xinbo Gao, Heng Yang, Yuxuan Du, Bo Han, Tongliang Liu

ICML 2022 Contrastive Learning with Boosted Memorization Zhihan Zhou, Jiangchao Yao, Yan-Feng Wang, Bo Han, Ya Zhang

NeurIPS 2022 Counterfactual Fairness with Partially Known Causal Graph Aoqi Zuo, Susan Wei, Tongliang Liu, Bo Han, Kun Zhang, Mingming Gong

ECCV 2022 EAGAN: Efficient Two-Stage Evolutionary Architecture Search for GANs Guohao Ying, Xin He, Bin Gao, Bo Han, Xiaowen Chu

ICML 2022 Estimating Instance-Dependent Bayes-Label Transition Matrix Using a Deep Neural Network Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu

NeurIPS 2022 Exact Shape Correspondence via 2D Graph Convolution Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Ma Kaili, Bo Han, Bo Li, James Cheng

ICLR 2022 Exploiting Class Activation Value for Partial-Label Learning Fei Zhang, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Tao Qin, Masashi Sugiyama

CLeaR 2022 Fair Classification with Instance-Dependent Label Noise Songhua Wu, Mingming Gong, Bo Han, Yang Liu, Tongliang Liu

ICML 2022 Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng

ICML 2022 Improving Adversarial Robustness via Mutual Information Estimation Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Xiaoyu Wang, Yibing Zhan, Tongliang Liu

CVPR 2022 Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation De Cheng, Tongliang Liu, Yixiong Ning, Nannan Wang, Bo Han, Gang Niu, Xinbo Gao, Masashi Sugiyama

ICMLW 2022 Invariance Principle Meets Out-of-Distribution Generalization on Graphs Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Ma Kaili, Binghui Xie, Tongliang Liu, Bo Han, James Cheng

NeurIPS 2022 Is Out-of-Distribution Detection Learnable? Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, Feng Liu

NeurIPS 2022 Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Ma Kaili, Binghui Xie, Tongliang Liu, Bo Han, James Cheng

JMLR 2022 Learning from Noisy Pairwise Similarity and Unlabeled Data Songhua Wu, Tongliang Liu, Bo Han, Jun Yu, Gang Niu, Masashi Sugiyama

JMLR 2022 Low-Rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization Quanming Yao, Yaqing Wang, Bo Han, James T. Kwok

ICLR 2022 Meta Discovery: Learning to Discover Novel Classes Given Very Limited Data Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, Gang Niu, Mingyuan Zhou, Masashi Sugiyama

ICML 2022 Modeling Adversarial Noise for Adversarial Training Dawei Zhou, Nannan Wang, Bo Han, Tongliang Liu

TMLR 2022 NoiLin: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Lizhen Cui, Gang Niu, Masashi Sugiyama

NeurIPS 2022 Pluralistic Image Completion with Gaussian Mixture Models Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li, Yibing Zhan, Bo Han, Tongliang Liu

NeurIPSW 2022 Pre-Training Robust Feature Extractor Against Clean-Label Data Poisoning Attacks Ting Zhou, Hanshu Yan, Lei Liu, Jingfeng Zhang, Bo Han

NeurIPS 2022 RSA: Reducing Semantic Shift from Aggressive Augmentations for Self-Supervised Learning Yingbin Bai, Erkun Yang, Zhaoqing Wang, Yuxuan Du, Bo Han, Cheng Deng, Dadong Wang, Tongliang Liu

ICLR 2022 Reliable Adversarial Distillation with Unreliable Teachers Jianing Zhu, Jiangchao Yao, Bo Han, Jingfeng Zhang, Tongliang Liu, Gang Niu, Jingren Zhou, Jianliang Xu, Hongxia Yang

ICLR 2022 Rethinking Class-Prior Estimation for Positive-Unlabeled Learning Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao

IJCAI 2022 Robust Weight Perturbation for Adversarial Training Chaojian Yu, Bo Han, Mingming Gong, Li Shen, Shiming Ge, Du Bo, Tongliang Liu

ICLR 2022 Sample Selection with Uncertainty of Losses for Learning with Noisy Labels Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama

TMLR 2022 SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long

NeurIPS 2022 Synergy-of-Experts: Collaborate to Improve Adversarial Robustness Sen Cui, Jingfeng Zhang, Jian Liang, Bo Han, Masashi Sugiyama, Changshui Zhang

NeurIPS 2022 Towards Lightweight Black-Box Attack Against Deep Neural Networks Chenghao Sun, Yonggang Zhang, Wan Chaoqun, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian

ICML 2022 Understanding Robust Overfitting of Adversarial Training and Beyond Chaojian Yu, Bo Han, Li Shen, Jun Yu, Chen Gong, Mingming Gong, Tongliang Liu

ICLR 2022 Understanding and Improving Graph Injection Attack by Promoting Unnoticeability Yongqiang Chen, Han Yang, Yonggang Zhang, Ma Kaili, Tongliang Liu, Bo Han, James Cheng

ICML 2022 Virtual Homogeneity Learning: Defending Against Data Heterogeneity in Federated Learning Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xin He, Bo Han, Xiaowen Chu

NeurIPS 2022 Watermarking for Out-of-Distribution Detection Qizhou Wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong, Tongliang Liu, Bo Han

ICML 2021 Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu

ICML 2021 Confidence Scores Make Instance-Dependent Label-Noise Learning Possible Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama

ICLR 2021 Geometry-Aware Instance-Reweighted Adversarial Training Jingfeng Zhang, Jianing Zhu, Gang Niu, Bo Han, Masashi Sugiyama, Mohan Kankanhalli

NeurIPS 2021 Instance-Dependent Label-Noise Learning Under a Structural Causal Model Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang

ICML 2021 Learning Diverse-Structured Networks for Adversarial Robustness Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang, Masashi Sugiyama

AAAI 2021 Learning with Group Noise Qizhou Wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong, Hongxia Yang, Bo Han

ICML 2021 Maximum Mean Discrepancy Test Is Aware of Adversarial Attacks Ruize Gao, Feng Liu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Masashi Sugiyama

ICML 2021 Pointwise Binary Classification with Pairwise Confidence Comparisons Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama

NeurIPS 2021 Probabilistic Margins for Instance Reweighting in Adversarial Training Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama

ICML 2021 Provably End-to-End Label-Noise Learning Without Anchor Points Xuefeng Li, Tongliang Liu, Bo Han, Gang Niu, Masashi Sugiyama

ICLR 2021 Robust Early-Learning: Hindering the Memorization of Noisy Labels Xiaobo Xia, Tongliang Liu, Bo Han, Chen Gong, Nannan Wang, Zongyuan Ge, Yi Chang

NeurIPS 2021 TOHAN: A One-Step Approach Towards Few-Shot Hypothesis Adaptation Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, William Cheung, James T. Kwok

AAAI 2021 Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model Qizhou Wang, Bo Han, Tongliang Liu, Gang Niu, Jian Yang, Chen Gong

ICML 2021 Towards Defending Against Adversarial Examples via Attack-Invariant Features Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao

NeurIPS 2021 Understanding and Improving Early Stopping for Learning with Noisy Labels Yingbin Bai, Erkun Yang, Bo Han, Yanhua Yang, Jiatong Li, Yinian Mao, Gang Niu, Tongliang Liu

NeurIPS 2021 Universal Semi-Supervised Learning Zhuo Huang, Chao Xue, Bo Han, Jian Yang, Chen Gong

IJCAI 2020 A Bi-Level Formulation for Label Noise Learning with Spectral Cluster Discovery Yijing Luo, Bo Han, Chen Gong

ICML 2020 Attacks Which Do Not Kill Training Make Adversarial Learning Stronger Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan Kankanhalli

AAAI 2020 Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling Chao Li, Mohammad Emtiyaz Khan, Zhun Sun, Gang Niu, Bo Han, Shengli Xie, Qibin Zhao

ECML-PKDD 2020 Confusable Learning for Large-Class Few-Shot Classification Bingcong Li, Bo Han, Zhuowei Wang, Jing Jiang, Guodong Long

NeurIPS 2020 Dual T: Reducing Estimation Error for Transition Matrix in Label-Noise Learning Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama

ICML 2020 Learning with Multiple Complementary Labels Lei Feng, Takuo Kaneko, Bo Han, Gang Niu, Bo An, Masashi Sugiyama

NeurIPS 2020 Part-Dependent Label Noise: Towards Instance-Dependent Label Noise Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama

NeurIPS 2020 Provably Consistent Partial-Label Learning Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama

ICML 2020 SIGUA: Forgetting May Make Learning with Noisy Labels More Robust Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor Tsang, Masashi Sugiyama

ICML 2020 Searching to Exploit Memorization Effect in Learning with Noisy Labels Quanming Yao, Hansi Yang, Bo Han, Gang Niu, James Tin-Yau Kwok

ICML 2020 Variational Imitation Learning with Diverse-Quality Demonstrations Voot Tangkaratt, Bo Han, Mohammad Emtiyaz Khan, Masashi Sugiyama

NeurIPS 2019 Are Anchor Points Really Indispensable in Label-Noise Learning? Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama

ICML 2019 Efficient Nonconvex Regularized Tensor Completion with Structure-Aware Proximal Iterations Quanming Yao, James Tin-Yau Kwok, Bo Han

ICML 2019 How Does Disagreement Help Generalization Against Label Corruption? Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor Tsang, Masashi Sugiyama

MLJ 2019 Millionaire: A Hint-Guided Approach for Crowdsourcing Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama

IJCAI 2019 Towards Robust ResNet: A Small Step but a Giant Leap Jingfeng Zhang, Bo Han, Laura Wynter, Bryan Kian Hsiang Low, Mohan S. Kankanhalli

ICCVW 2019 VisDrone-SOT2019: The Vision Meets Drone Single Object Tracking Challenge Results Dawei Du, Yue Zhang, Liefeng Bo, Hailin Shi, Rui Zhu, Bo Han, Chunhui Zhang, Guizhong Liu, Han Wu, Hao Wen, Haoran Wang, Pengfei Zhu, Jiaqing Fan, Jie Chen, Jie Gao, Jie Zhang, Jinghao Zhou, Jinliu Zhou, Jinwang Wang, Jiuqing Wan, Josef Kittler, Kaihua Zhang, Longyin Wen, Kaiqi Huang, Kang Yang, Kangkai Zhang, Lianghua Huang, Lijun Zhou, Lingling Shi, Lu Ding, Ning Wang, Peng Wang, Qintao Hu, Xiao Bian, Robert Laganière, Ruiyan Ma, Ruohan Zhang, Shanrong Zou, Shengwei Zhao, Shengyang Li, Shengyin Zhu, Shikun Li, Shiming Ge, Shiyu Xuan, Haibin Ling, Tianyang Xu, Ting He, Wei Shi, Wei Song, Weiming Hu, Wenhua Zhang, Wenjun Zhu, Xi Yu, Xianhai Wang, Xiaojun Wu, Qinghua Hu, Xiaotong Li, Xiaoxue Li, Xiaoyue Yin, Xin Zhang, Xin Zhao, Xizhe Xue, Xu Lei, Xueyuan Yang, Yanjie Gao, Yanyun Zhao, Jiayu Zheng, Yinda Xu, Ying Li, Yong Wang, Yong Yang, Yuting Yang, Yuxuan Li, Zeyu Wang, Zhenhua Feng, Zhipeng Zhang, Zhiyong Yu, Tao Peng, Zhizhao Duan, Zhuojin Sun, Xinyao Wang

NeurIPS 2018 Co-Teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, Masashi Sugiyama

NeurIPS 2018 Masking: A New Perspective of Noisy Supervision Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor Tsang, Ya Zhang, Masashi Sugiyama

MLJ 2018 Robust Plackett-Luce Model for K-Ary Crowdsourced Preferences Bo Han, Yuangang Pan, Ivor W. Tsang

MLJ 2018 Stagewise Learning for Noisy K-Ary Preferences Yuangang Pan, Bo Han, Ivor W. Tsang

ECML-PKDD 2016 On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent Bo Han, Ivor W. Tsang, Ling Chen

JAIR 2014 Text-Based Twitter User Geolocation Prediction Bo Han, Paul Cook, Timothy Baldwin