An, Bang

29 publications

NeurIPS 2025 A Technical Report on “Erasing the Invisible”: The 2024 NeurIPS Competition on Stress Testing Image Watermarks Mucong Ding, Bang An, Tahseen Rabbani, Chenghao Deng, Anirudh Satheesh, Souradip Chakraborty, Mehrdad Saberi, Yuxin Wen, Kyle Rui Sang, Aakriti Agrawal, Xuandong Zhao, Mo Zhou, Mary-Anne Hartley, Lei Li, Yu-Xiang Wang, Vishal M. Patel, Soheil Feizi, Tom Goldstein, Furong Huang

ICLRW 2025 AegisLLM: Scaling Agentic Systems for Self-Reflective Defense in LLM Security Zikui Cai, Shayan Shabihi, Bang An, Zora Che, Brian R. Bartoldson, Bhavya Kailkhura, Tom Goldstein, Furong Huang

AAAI 2025 Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data? Michael-Andrei Panaitescu-Liess, Zora Che, Bang An, Yuancheng Xu, Pankayaraj Pathmanathan, Souradip Chakraborty, Sicheng Zhu, Tom Goldstein, Furong Huang

ICLR 2025 GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-Time Alignment Yuancheng Xu, Udari Madhushani Sehwag, Alec Koppel, Sicheng Zhu, Bang An, Furong Huang, Sumitra Ganesh

AAAI 2025 GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models Through Statistically-Guided Geo-Prototyping Bang An, Xun Zhou, Zirui Zhou, Ronilo J. Ragodos, Zenglin Xu, Jun Luo

NeurIPS 2024 Alignment at Pre-Training! Towards Native Alignment for Arabic LLMs Juhao Liang, Zhenyang Cai, Jianqing Zhu, Huang Huang, Kewei Zong, Bang An, Abdulmohsen Alharthi, Juncai He, Lian Zhang, Haizhou Li, Benyou Wang, Jinchao Xu

ICMLW 2024 Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models Bang An, Sicheng Zhu, Ruiyi Zhang, Michael-Andrei Panaitescu-Liess, Yuancheng Xu, Furong Huang

ICMLW 2024 Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data? Michael-Andrei Panaitescu-Liess, Zora Che, Bang An, Yuancheng Xu, Pankayaraj Pathmanathan, Souradip Chakraborty, Sicheng Zhu, Tom Goldstein, Furong Huang

NeurIPSW 2024 Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data? Michael-Andrei Panaitescu-Liess, Zora Che, Bang An, Yuancheng Xu, Pankayaraj Pathmanathan, Souradip Chakraborty, Sicheng Zhu, Tom Goldstein, Furong Huang

ICLR 2024 PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang

NeurIPSW 2024 PoisonedParrot: Subtle Data Poisoning Attacks to Elicit Copyright-Infringing Content from Large Language Models Michael-Andrei Panaitescu-Liess, Pankayaraj Pathmanathan, Yigitcan Kaya, Zora Che, Bang An, Sicheng Zhu, Aakriti Agrawal, Furong Huang

ICML 2024 Position: On the Possibilities of AI-Generated Text Detection Souradip Chakraborty, Amrit Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, Furong Huang

AAAI 2024 Referee-Meta-Learning for Fast Adaptation of Locational Fairness Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He, Han Bao, Bang An, Xun Zhou

ICLR 2024 SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang

ICML 2024 WAVES: Benchmarking the Robustness of Image Watermarks Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang

ICLRW 2024 WAVES: Benchmarking the Robustness of Image Watermarks Mucong Ding, Tahseen Rabbani, Bang An, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang

NeurIPSW 2023 AutoDAN: Automatic and Interpretable Adversarial Attacks on Large Language Models Sicheng Zhu, Ruiyi Zhang, Bang An, Gang Wu, Joe Barrow, Zichao Wang, Furong Huang, Ani Nenkova, Tong Sun

ICMLW 2023 C-Disentanglement: Discovering Causally-Independent Generative Factors Under an Inductive Bias of Confounder Xiaoyu Liu, Jiaxin Yuan, Bang An, Yuancheng Xu, Yifan Yang, Furong Huang

NeurIPS 2023 C-Disentanglement: Discovering Causally-Independent Generative Factors Under an Inductive Bias of Confounder Xiaoyu Liu, Jiaxin Yuan, Bang An, Yuancheng Xu, Yifan Yang, Furong Huang

ICML 2023 Learning Unforeseen Robustness from Out-of-Distribution Data Using Equivariant Domain Translator Sicheng Zhu, Bang An, Furong Huang, Sanghyun Hong

ICLRW 2023 Learning Unforeseen Robustness from Out-of-Distribution Data Using Equivariant Domain Translator Sicheng Zhu, Bang An, Furong Huang, Sanghyun Hong

ICMLW 2023 More Context, Less Distraction: Improving Zero-Shot Inference of CLIP by Inferring and Describing Spurious Features Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang

NeurIPS 2023 SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data Bang An, Xun Zhou, Yongjian Zhong, Tianbao Yang

NeurIPSW 2022 GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint Paiheng Xu, Yuhang Zhou, Bang An, Wei Ai, Furong Huang

NeurIPS 2022 Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang

NeurIPSW 2022 Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity Mucong Ding, Tahseen Rabbani, Bang An, Evan Z Wang, Furong Huang

NeurIPS 2022 Transferring Fairness Under Distribution Shifts via Fair Consistency Regularization Bang An, Zora Che, Mucong Ding, Furong Huang

NeurIPS 2021 Understanding the Generalization Benefit of Model Invariance from a Data Perspective Sicheng Zhu, Bang An, Furong Huang

IJCAI 2020 Deep Semantic Compliance Advisor for Unstructured Document Compliance Checking Honglei Guo, Bang An, Zhili Guo, Zhong Su