Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes. - Sanghyun Hong 001; Michael-Andrei Panaitescu-Liess; Yigitcan Kaya; Tudor Dumitras (NeurIPS, 2021)

More Context, Less Distraction: Visual Classification by Inferring and Conditioning on Contextual Attributes. - Bang An 001; Sicheng Zhu; Michael-Andrei Panaitescu-Liess; Chaithanya Kumar Mummadi; Furong Huang (CoRR, 2023)

PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts. - Bang An 001; Sicheng Zhu; Michael-Andrei Panaitescu-Liess; Chaithanya Kumar Mummadi; Furong Huang (ICLR, 2024)

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 (ICLR, 2024)

Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models. - Bang An 001; Sicheng Zhu; Ruiyi Zhang 002; Michael-Andrei Panaitescu-Liess; Yuancheng Xu; Furong Huang (CoRR, 2024)

AdvBDGen: Adversarially Fortified Prompt-Specific Fuzzy Backdoor Generator Against LLM Alignment. - Pankayaraj Pathmanathan; Udari Madhushani Sehwag; Michael-Andrei Panaitescu-Liess; Furong Huang (CoRR, 2024)

Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data? - Michael-Andrei Panaitescu-Liess; Zora Che; Bang An 001; Yuancheng Xu; Pankayaraj Pathmanathan; Souradip Chakraborty; Sicheng Zhu; Tom Goldstein; Furong Huang (AAAI, 2025)

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 001; Sicheng Zhu; Aakriti Agrawal; Furong Huang (NAACL (Long Papers), 2025)