| 2026 | AAAI | Domain-Auxiliary Infrared Moving Small Target Detection by Learning to Overlook Domain Discrepancy. | Shengjia Chen, Luping Ji, Shuang Peng, Sicheng Zhu, Mao Ye |
| 2026 | AAAI | SeViL: Semi-supervised Vision-Language Learning with Text Prompt Guiding for Moving Infrared Small Target Detection. | Weiwei Duan, Luping Ji, Jianghong Huang, Sicheng Zhu |
| 2026 | AAAI | Cross-domain Joint Learning with Prototype-guided Mixture-of-Experts for Infrared Moving Small Target Detection. | Weiwei Duan, Luping Ji, Jianghong Huang, Sicheng Zhu, Mao Ye |
| 2025 | AAAI | 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 |
| 2025 | ICLR | 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 |
| 2025 | NAACL | 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 |
| 2024 | ICLR | PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts. | Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang |
| 2024 | ICLR | Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds. | Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Sicheng Zhu, Furong Huang, Tudor Dumitras |
| 2024 | ICML | 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 |
| 2024 | ICML | Position: On the Possibilities of AI-Generated Text Detection. | Souradip Chakraborty, Amrit S. Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, Furong Huang |
| 2023 | ICML | Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator. | Sicheng Zhu, Bang An, Furong Huang, Sanghyun Hong |
| 2020 | ICML | Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization. | Sicheng Zhu, Xiao Zhang, David Evans |