Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks. - Yonggang Zhang 003; Ya Li; Tongliang Liu; Xinmei Tian 001 (ICML, 2020)

Principal Component Adversarial Example. - Yonggang Zhang 003; Xinmei Tian 001; Ya Li; Xinchao Wang; Dacheng Tao (IEEE Trans. Image Process., 2020)

Class-Disentanglement and Applications in Adversarial Detection and Defense. - Kaiwen Yang; Tianyi Zhou 001; Yonggang Zhang 003; Xinmei Tian 001; Dacheng Tao (NeurIPS, 2021)

Prompt Distribution Learning. - Yuning Lu; Jianzhuang Liu; Yonggang Zhang 003; Yajing Liu; Xinmei Tian 001 (CVPR, 2022)

Meta Convolutional Neural Networks for Single Domain Generalization. - Chaoqun Wan; Xu Shen 001; Yonggang Zhang 003; Zhiheng Yin; Xinmei Tian 001; Feng Gao; Jianqiang Huang; Xian-Sheng Hua 001 (CVPR, 2022)

Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. - Yongqiang Chen 002; Han Yang 002; Yonggang Zhang 003; Kaili Ma 001; Tongliang Liu; Bo Han 003; James Cheng (ICLR, 2022)

Adversarial Robustness Through the Lens of Causality. - Yonggang Zhang 003; Mingming Gong; Tongliang Liu; Gang Niu 001; Xinmei Tian 001; Bo Han 003; Bernhard Schölkopf; Kun Zhang 001 (ICLR, 2022)

Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning. - Zhenheng Tang; Yonggang Zhang 003; Shaohuai Shi; Xin He; Bo Han 003; Xiaowen Chu 001 (ICML, 2022)

Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs. - Yongqiang Chen 002; Yonggang Zhang 003; Yatao Bian; Han Yang 002; Kaili Ma 001; Binghui Xie; Tongliang Liu; Bo Han 003; James Cheng (NeurIPS, 2022)

Towards Lightweight Black-Box Attack Against Deep Neural Networks. - Chenghao Sun; Yonggang Zhang 003; Chaoqun Wan; Qizhou Wang; Ya Li; Tongliang Liu; Bo Han 003; Xinmei Tian 001 (NeurIPS, 2022)

Watermarking for Out-of-distribution Detection. - Qizhou Wang; Feng Liu 003; Yonggang Zhang 003; Jing Zhang 037; Chen Gong 002; Tongliang Liu; Bo Han 003 (NeurIPS, 2022)

Invariance Principle Meets Out-of-Distribution Generalization on Graphs. - Yongqiang Chen 002; Yonggang Zhang 003; Han Yang 002; Kaili Ma 001; Binghui Xie; Tongliang Liu; Bo Han 003; James Cheng (CoRR, 2022)

Pareto Invariant Risk Minimization. - Yongqiang Chen 002; Kaiwen Zhou; Yatao Bian; Binghui Xie; Kaili Ma 001; Yonggang Zhang 003; Han Yang 002; Bo Han 003; James Cheng (CoRR, 2022)

Towards Lightweight Black-Box Attacks against Deep Neural Networks. - Chenghao Sun; Yonggang Zhang 003; Chaoqun Wan; Qizhou Wang; Ya Li; Tongliang Liu; Bo Han 003; Xinmei Tian 001 (CoRR, 2022)

Hard Sample Matters a Lot in Zero-Shot Quantization. - Huantong Li; Xiangmiao Wu; Fanbing Lv; Daihai Liao; Thomas H. Li; Yonggang Zhang 003; Bo Han 003; Mingkui Tan (CVPR, 2023)

Continual Named Entity Recognition without Catastrophic Forgetting. - Duzhen Zhang; Wei Cong; Jiahua Dong 001; Yahan Yu; Xiuyi Chen; Yonggang Zhang 003; Zhen Fang 001 (EMNLP, 2023)

Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. - Yongqiang Chen 002; Kaiwen Zhou; Yatao Bian; Binghui Xie; Bingzhe Wu; Yonggang Zhang 003; Kaili Ma 001; Han Yang 002; Peilin Zhao; Bo Han 003; James Cheng (ICLR, 2023)

Moderately Distributional Exploration for Domain Generalization. - Rui Dai; Yonggang Zhang 003; Zhen Fang 001; Bo Han 003; Xinmei Tian 001 (ICML, 2023)

Learning to Augment Distributions for Out-of-distribution Detection. - Qizhou Wang; Zhen Fang 001; Yonggang Zhang 003; Feng Liu 003; Yixuan Li 001; Bo Han 003 (NeurIPS, 2023)

SODA: Robust Training of Test-Time Data Adaptors. - Zige Wang; Yonggang Zhang 003; Zhen Fang 001; Long Lan; Wenjing Yang 002; Bo Han 003 (NeurIPS, 2023)

Invariant Learning via Probability of Sufficient and Necessary Causes. - Mengyue Yang; Yonggang Zhang 003; Zhen Fang 001; Yali Du 001; Furui Liu; Jean-Francois Ton; Jianhong Wang; Jun Wang 012 (NeurIPS, 2023)

FedFed: Feature Distillation against Data Heterogeneity in Federated Learning. - Zhiqin Yang; Yonggang Zhang 003; Yu Zheng 021; Xinmei Tian 001; Hao Peng; Tongliang Liu; Bo Han 003 (NeurIPS, 2023)

FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training. - Zhenheng Tang; Xiaowen Chu 001; Ryan Yide Ran; Sunwoo Lee 001; Shaohuai Shi; Yonggang Zhang 003; Yuxin Wang 003; Alex Qiaozhong Liang; Salman Avestimehr; Chaoyang He 001 (CoRR, 2023)

Invariant Learning via Probability of Sufficient and Necessary Causes. - Mengyue Yang; Zhen Fang 001; Yonggang Zhang 003; Yali Du 001; Furui Liu; Jean-Francois Ton; Jun Wang 012 (CoRR, 2023)

Federated Learning with Extremely Noisy Clients via Negative Distillation. - Yang Lu 009; Lin Chen; Yonggang Zhang 003; Yiliang Zhang; Bo Han 003; Yiu-ming Cheung; Hanzi Wang (AAAI, 2024)

Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting. - Rong Dai; Yonggang Zhang 003; Ang Li; Tongliang Liu; Xun Yang 001; Bo Han 003 (ICLR, 2024)

Out-of-Distribution Detection with Negative Prompts. - Jun Nie; Yonggang Zhang 003; Zhen Fang 001; Tongliang Liu; Bo Han 003; Xinmei Tian 001 (ICLR, 2024)

ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection. - Bo Peng; Yadan Luo; Yonggang Zhang 003; Yixuan Li 001; Zhen Fang 001 (ICLR, 2024)

FedImpro: Measuring and Improving Client Update in Federated Learning. - Zhenheng Tang; Yonggang Zhang 003; Shaohuai Shi; Xinmei Tian 001; Tongliang Liu; Bo Han 003; Xiaowen Chu 001 (ICLR, 2024)

Robust Training of Federated Models with Extremely Label Deficiency. - Yonggang Zhang 003; Zhiqin Yang; Xinmei Tian 001; Nannan Wang 001; Tongliang Liu; Bo Han 003 (ICLR, 2024)

NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation. - Pengfei Zheng; Yonggang Zhang 003; Zhen Fang 001; Tongliang Liu; Defu Lian; Bo Han 003 (ICLR, 2024)

From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning. - Wei Chen 005; Zhen Huang 007; Liang Xie 003; Binbin Lin; Houqiang Li; Le Lu 001; Xinmei Tian 001; Deng Cai 001; Yonggang Zhang 003; Wenxiao Wang 001; Xu Shen 001; Jieping Ye (ICML, 2024)

Interpreting and Improving Large Language Models in Arithmetic Calculation. - Wei Zhang; Chaoqun Wan; Yonggang Zhang 003; Yiu-ming Cheung; Xinmei Tian 001; Xu Shen 001; Jieping Ye (ICML, 2024)

Component-Level Oracle Bone Inscription Retrieval. - Zhikai Hu; Yiu-ming Cheung; Yonggang Zhang 003; Peiying Zhang 003; Puiling Tang (ICMR, 2024)

Learning to Shape In-distribution Feature Space for Out-of-distribution Detection. - Yonggang Zhang 003; Jie Lu 001; Bo Peng; Zhen Fang 001; Yiu-ming Cheung (NeurIPS, 2024)

FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion. - Zhenheng Tang; Yonggang Zhang 003; Peijie Dong; Yiu-ming Cheung; Amelie Chi Zhou; Bo Han 003; Xiaowen Chu 001 (NeurIPS, 2024)

Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control. - Yuxin Xiao; Chaoqun Wan; Yonggang Zhang 003; Wenxiao Wang 001; Binbin Lin; Xiaofei He 001; Xu Shen 001; Jieping Ye (NeurIPS, 2024)

Rethinking Improved Privacy-Utility Trade-off with Pre-existing Knowledge for DP Training. - Yu Zheng 021; Wenchao Zhang 001; Yonggang Zhang 003; Wei Song; Kai Zhou 001; Bo Han 003 (CoRR, 2024)

Detecting Discrepancies Between AI-Generated and Natural Images Using Uncertainty. - Jun Nie; Yonggang Zhang 003; Tongliang Liu; Yiu-ming Cheung; Bo Han 003; Xinmei Tian 001 (CoRR, 2024)

Expert-level diagnosis of pediatric posterior fossa tumors via consistency calibration. - Chenghao Sun; Zihan Yan; Yonggang Zhang 003; Xinmei Tian 001; Jian Gong (Knowl. Based Syst., 2024)

Component-Level Segmentation for Oracle Bone Inscription Decipherment. - Zhikai Hu; Yiu-ming Cheung; Yonggang Zhang 003; Peiying Zhang 003; Puiling Tang (AAAI, 2025)

Interpret and Improve In-Context Learning via the Lens of Input-Label Mappings. - Chenghao Sun; Zhen Huang 007; Yonggang Zhang 003; Le Lu 001; Houqiang Li; Xinmei Tian 001; Xu Shen 001; Jieping Ye (ACL (1), 2025)

Tracing and Dissecting How LLMs Recall Factual Knowledge for Real World Questions. - Yiqun Wang; Chaoqun Wan; Sile Hu; Yonggang Zhang 003; Xiang Tian 002; Yaowu Chen; Xu Shen 001; Jieping Ye (ACL (1), 2025)

Characterizing Submanifold Region for Out-of-Distribution Detection: (Extended Abstract). - Xuhui Li; Zhen Fang 001; Yonggang Zhang 003; Ning Ma; Jiajun Bu; Bo Han 003; Haishuai Wang (ICDE, 2025)

MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection. - Zhuoxiao Chen; Junjie Meng; Mahsa Baktashmotlagh; Yonggang Zhang 003; Zi Huang; Yadan Luo (ICLR, 2025)

Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs. - Rui Dai; Sile Hu; Xu Shen 001; Yonggang Zhang 003; Xinmei Tian 001; Jieping Ye (ICLR, 2025)

Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection. - Lei Shen; Zhenheng Tang; Lijun Wu; Yonggang Zhang 003; Xiaowen Chu 001; Tao Qin; Bo Han 003 (ICLR, 2025)

Distributional Prototype Learning for Out-of-distribution Detection. - Bo Peng; Jie Lu 001; Yonggang Zhang 003; Guangquan Zhang 001; Zhen Fang 001 (KDD (1), 2025)

Mitigating Forgetting in Adapting Pre-trained Language Models to Text Processing Tasks via Consistency Alignment. - Jianqi Gao 001; Hao Wu 087; Yiu-ming Cheung; Jian Cao 001; Hang Yu 006; Yonggang Zhang 003 (WWW, 2025)

MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction. - Yue Yang; Kairui Guo; Yonggang Zhang 003; Zhen Fang 001; Hua Lin; Mark Grosser; Deon Venter; Weihai Lu; Mengjia Wu; Dennis Cordato; Guangquan Zhang 001; Jie Lu 001 (Briefings Bioinform., 2025)

InsGNN: Interpretable spatio-temporal graph neural networks via information bottleneck. - Hui Fang; Haishuai Wang; Yang Gao 024; Yonggang Zhang 003; Jiajun Bu; Bo Han 003; Hui Lin (Inf. Fusion, 2025)

SENA: Leveraging set-level consistency adversarial learning for robust pre-trained language model adaptation. - Jianqi Gao 001; Jian Cao 001; Hang Yu 006; Yonggang Zhang 003; Zhen Fang 001 (Knowl. Based Syst., 2025)

Consistent prompt learning for vision-language models. - Yonggang Zhang 003; Xinmei Tian 001 (Knowl. Based Syst., 2025)

Shaping pre-trained language models for task-specific embedding generation via consistency calibration. - Jianqi Gao 001; Hang Yu 006; Yiu-ming Cheung; Jian Cao 001; Raymond Chi-Wing Wong; Yonggang Zhang 003 (Neural Networks, 2025)

Characterizing Submanifold Region for Out-of-Distribution Detection. - Xuhui Li; Zhen Fang 001; Yonggang Zhang 003; Ning Ma; Jiajun Bu; Bo Han 003; Haishuai Wang (IEEE Trans. Knowl. Data Eng., 2025)

Out-of-Distribution Detection with Virtual Outlier Smoothing. - Jun Nie; Yadan Luo; Shanshan Ye; Yonggang Zhang 003; Xinmei Tian 001; Zhen Fang 001 (Int. J. Comput. Vis., 2025)

Enhancing Target-unspecific Tasks through a Features Matrix. - Fangming Cui; Yonggang Zhang 003; Xuan Wang; Xinmei Tian 001; Jun Yu (CoRR, 2025)

Semantic-guided Fine-tuning of Foundation Model for Long-tailed Visual Recognition. - Yufei Peng; Yonggang Zhang 003; Yiu-ming Cheung (CoRR, 2025)