Zhang, Yonggang

41 publications

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

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

ICML 2025 Enhancing Target-Unspecific Tasks Through a Features Matrix Fangming Cui, Yonggang Zhang, Xuan Wang, Xinmei Tian, Jun Yu

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

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

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 Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs Rui Dai, Sile Hu, Xu Shen, Yonggang Zhang, Xinmei Tian, Jieping Ye

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

NeurIPS 2025 Towards Generalizable Detector for Generated Image Qianshu Cai, Chao Wu, Yonggang Zhang, Jun Yu, Xinmei Tian

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

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

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

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

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

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

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

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

ICML 2024 Interpreting and Improving Large Language Models in Arithmetic Calculation Wei Zhang, Chaoqun Wan, Yonggang Zhang, Yiu-Ming Cheung, Xinmei Tian, Xu Shen, Jieping Ye

NeurIPS 2024 Learning to Shape In-Distribution Feature Space for Out-of-Distribution Detection Yonggang Zhang, Jie Lu, Bo Peng, Zhen Fang, Yiu-ming Cheung

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

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

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

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

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

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

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

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

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

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

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 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

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

CVPR 2022 Prompt Distribution Learning Yuning Lu, Jianzhuang Liu, Yonggang Zhang, Yajing Liu, Xinmei Tian

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

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

NeurIPS 2021 Class-Disentanglement and Applications in Adversarial Detection and Defense Kaiwen Yang, Tianyi Zhou, Yonggang Zhang, Xinmei Tian, Dacheng Tao

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