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2020 – today
- 2024
[c3]Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang:
PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts. ICLR 2024- [c2]Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Sicheng Zhu, Furong Huang, Tudor Dumitras:
Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds. ICLR 2024 - [i5]Michael-Andrei Panaitescu-Liess, Zora Che, Bang An, Yuancheng Xu, Pankayaraj Pathmanathan, Souradip Chakraborty, Sicheng Zhu, Tom Goldstein, Furong Huang:
Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data? CoRR abs/2407.17417 (2024) - [i4]Bang An, Sicheng Zhu, Ruiyi Zhang, Michael-Andrei Panaitescu-Liess, Yuancheng Xu, Furong Huang:
Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models. CoRR abs/2409.00598 (2024) - [i3]Pankayaraj Pathmanathan, Udari Madhushani Sehwag, Michael-Andrei Panaitescu-Liess, Furong Huang:
AdvBDGen: Adversarially Fortified Prompt-Specific Fuzzy Backdoor Generator Against LLM Alignment. CoRR abs/2410.11283 (2024) - 2023
- [i2]Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang:
More Context, Less Distraction: Visual Classification by Inferring and Conditioning on Contextual Attributes. CoRR abs/2308.01313 (2023) - 2021
- [c1]Sanghyun Hong, Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Tudor Dumitras:
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes. NeurIPS 2021: 9303-9316 - [i1]Sanghyun Hong, Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Tudor Dumitras:
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes. CoRR abs/2110.13541 (2021)
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