Wang, Haohan

40 publications

TMLR 2026 Large Language Model-Based Data Science Agent: A Survey Ke Chen, Peiran Wang, Yaoning Yu, Xianyang Zhan, Haohan Wang

WACV 2025 An Investigation on LLMs' Visual Understanding Ability Using SVG for Image-Text Bridging Mu Cai, Zeyi Huang, Yuheng Li, Utkarsh Ojha, Haohan Wang, Yong Jae Lee

CPAL 2025 Approximate Nullspace Augmented Finetuning for Robust Vision Transformers Haoyang Liu, Aditya Singh, Yijiang Li, Haohan Wang

ICCV 2025 Customizing Domain Adapters for Domain Generalization Yuyang Ji, Zeyi Huang, Haohan Wang, Yong Jae Lee

ICCV 2025 Dataset Distillation via the Wasserstein Metric Haoyang Liu, Yijiang Li, Tiancheng Xing, Peiran Wang, Vibhu Dalal, Luwei Li, Jingrui He, Haohan Wang

NeurIPS 2025 Evaluating the Inductive Abilities of Large Language Models: Why Chain-of-Thought Reasoning Sometimes Hurts More than Helps Haibo Jin, Peiyan Zhang, Man Luo, Haohan Wang

ICLR 2025 Examining Alignment of Large Language Models Through Representative Heuristics: The Case of Political Stereotypes Sullam Jeoung, Yubin Ge, Haohan Wang, Jana Diesner

ICCV 2025 Improving Noise Efficiency in Privacy-Preserving Dataset Distillation Runkai Zheng, Vishnu Asutosh Dasu, Yinong Oliver Wang, Haohan Wang, Fernando De La Torre

MLJ 2025 Re-Assessing Accuracy Degradation: A Framework for Understanding DNN Behavior on Similar-but-Non-Identical Test Datasets Esla Timothy Anzaku, Haohan Wang, Ajiboye Babalola, Arnout Van Messem, Wesley De Neve

ICML 2025 Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization Peiyan Zhang, Haibo Jin, Leyang Hu, Xinnuo Li, Liying Kang, Man Luo, Yangqiu Song, Haohan Wang

AAAI 2025 Towards Adversarially Robust Dataset Distillation by Curvature Regularization Eric Xue, Yijiang Li, Haoyang Liu, Peiran Wang, Yifan Shen, Haohan Wang

ECCV 2024 CatchBackdoor: Backdoor Detection via Critical Trojan Neural Path Fuzzing Haibo Jin, Ruoxi Chen, Jinyin Chen, Haibin Zheng, Yang Zhang, Haohan Wang

TMLR 2024 Choosing Wisely and Learning Deeply: Selective Cross-Modality Distillation via CLIP for Domain Generalization Jixuan Leng, Yijiang Li, Haohan Wang

ECCV 2024 EditShield: Protecting Unauthorized Image Editing by Instruction-Guided Diffusion Models Ruoxi Chen, Haibo Jin, Yixin Liu, Jinyin Chen, Haohan Wang, Lichao Sun

ICLR 2024 Foundation Model-Oriented Robustness: Robust Image Model Evaluation with Pretrained Models Peiyan Zhang, Haoyang Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang

ICLRW 2024 GUARD: Role-Playing to Generate Natural-Language Jailbreakings to Test Guideline Adherence of Large Language Models Haibo Jin, Ruoxi Chen, Andy Zhou, Yang Zhang, Haohan Wang

NeurIPS 2024 Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters Haibo Jin, Andy Zhou, Joe D. Menke, Haohan Wang

ICLRW 2024 Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang

ICML 2024 Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang

NeurIPS 2024 Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks Andy Zhou, Bo Li, Haohan Wang

ICLRW 2024 Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks Andy Zhou, Bo Li, Haohan Wang

ECCV 2024 Simple Unsupervised Knowledge Distillation with Space Similarity Aditya Singh, Haohan Wang

ECCV 2024 Towards Reliable Advertising Image Generation Using Human Feedback Zhenbang Du, Wei Feng, Haohan Wang, Yaoyu Li, Jingsen Wang, Jian Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junsheng Jin, Junjie Shen, Zhangang Lin, Jingping Shao

TMLR 2024 Towards Understanding Adversarial Transferability in Federated Learning Yijiang Li, Ying Gao, Haohan Wang

NeurIPSW 2024 ZOOPFL: Exploring Black-Box Foundation Models for Personalized Federated Learning Wang Lu, Hao Yu, Jindong Wang, Damien Teney, Haohan Wang, Yao Zhu, Yiqiang Chen, Qiang Yang, Xing Xie, Xiangyang Ji

ICCV 2023 A Sentence Speaks a Thousand Images: Domain Generalization Through Distilling CLIP with Language Guidance Zeyi Huang, Andy Zhou, Zijian Ling, Mu Cai, Haohan Wang, Yong Jae Lee

NeurIPS 2023 Adaptive Test-Time Personalization for Federated Learning Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He

AAAI 2023 Calibrated Teacher for Sparsely Annotated Object Detection Haohan Wang, Liang Liu, Boshen Zhang, Jiangning Zhang, Wuhao Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang

NeurIPS 2023 Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang

ICML 2023 Optimizing the Collaboration Structure in Cross-Silo Federated Learning Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He

AAAI 2023 Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection Kun Xiang, Xing Zhang, Jinwen She, Jinpeng Liu, Haohan Wang, Shiqi Deng, Shancheng Jiang

IJCAI 2022 Iterative Few-Shot Semantic Segmentation from Image Label Text Haohan Wang, Liang Liu, Wuhao Zhang, Jiangning Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang

CVPR 2022 The Two Dimensions of Worst-Case Training and Their Integrated Effect for Out-of-Domain Generalization Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing

UAI 2022 Toward Learning Human-Aligned Cross-Domain Robust Models by Countering Misaligned Features Haohan Wang, Zeyi Huang, Hanlin Zhang, Yong Jae Lee, Eric P. Xing

NeurIPS 2021 Robust Contrastive Learning Using Negative Samples with Diminished Semantics Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, David Jacobs

ECCV 2020 Self-Challenging Improves Cross-Domain Generalization Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang

ICLR 2020 Smooth Kernels Improve Adversarial Robustness and Perceptually-Aligned Gradients Haohan Wang, Xindi Wu, Songwei Ge, Zachary C. Lipton, Eric P. Xing

NeurIPS 2019 Learning Robust Global Representations by Penalizing Local Predictive Power Haohan Wang, Songwei Ge, Zachary Lipton, Eric P Xing

ICLR 2019 Learning Robust Representations by Projecting Superficial Statistics Out Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing

AAAI 2019 What if We Simply Swap the Two Text Fragments? a Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks Haohan Wang, Da Sun, Eric P. Xing