Sihui Dai - RankMe

21 papers A* 8Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Adapting to Evolving Adversaries with Regularized Continual Robust Training. ICML Sihui Dai, Christian Cianfarani, Vikash Sehwag, Prateek Mittal, Arjun Nitin Bhagoji
2025	J	`jnl`	Adapting to Evolving Adversaries with Regularized Continual Robust Training. CoRR Sihui Dai, Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Prateek Mittal
2025	J	`jnl`	Can Memory-Augmented Language Models Generalize on Reasoning-in-a-Haystack Tasks? CoRR Payel Das, Ching-Yun Ko, Sihui Dai, Georgios Kollias, Subhajit Chaudhury, Aurélie C. Lozano
2024	A*	`conf`	Larimar: Large Language Models with Episodic Memory Control. ICML Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarathkrishna Swaminathan, Sihui Dai, Aurélie C. Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jirí Navrátil, Soham Dan, Pin-Yu Chen
2024	J	`jnl`	Larimar: Large Language Models with Episodic Memory Control. CoRR Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarath Swaminathan, Sihui Dai, Aurélie C. Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jirí Navrátil, Soham Dan, Pin-Yu Chen
2024	A*	`conf`	PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses. USENIX Security Symposium Chong Xiang, Tong Wu, Sihui Dai, Jonathan Petit, Suman Jana, Prateek Mittal
2024	J	`jnl`	Position Paper: Beyond Robustness Against Single Attack Types. CoRR Sihui Dai, Chong Xiang, Tong Wu, Prateek Mittal
2023	A*	`conf`	Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker. NeurIPS Sihui Dai, Wenxin Ding, Arjun Nitin Bhagoji, Daniel Cullina, Heather Zheng, Ben Zhao, Prateek Mittal
2023	J	`jnl`	Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker. CoRR Sihui Dai, Wenxin Ding, Arjun Nitin Bhagoji, Daniel Cullina, Ben Y. Zhao, Haitao Zheng, Prateek Mittal
2023	A*	`conf`	MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. ICML Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal
2023	J	`jnl`	MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. CoRR Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal
2023	J	`jnl`	PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses. CoRR Chong Xiang, Tong Wu, Sihui Dai, Jonathan Petit, Suman Jana, Prateek Mittal
2022	A*	`conf`	Formulating Robustness Against Unforeseen Attacks. NeurIPS Sihui Dai, Saeed Mahloujifar, Prateek Mittal
2022	J	`jnl`	Formulating Robustness Against Unforeseen Attacks. CoRR Sihui Dai, Saeed Mahloujifar, Prateek Mittal
2022	—	`conf`	Parameterizing Activation Functions for Adversarial Robustness. SP (Workshops) Sihui Dai, Saeed Mahloujifar, Prateek Mittal
2022	A*	`conf`	Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? ICLR Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal
2021	J	`jnl`	Improving Adversarial Robustness Using Proxy Distributions. CoRR Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal
2021	J	`jnl`	Parameterizing Activation Functions for Adversarial Robustness. CoRR Sihui Dai, Saeed Mahloujifar, Prateek Mittal
2020	A*	`conf`	Neural Networks with Recurrent Generative Feedback. NeurIPS Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan M. Nguyen, Doris Y. Tsao, Anima Anandkumar
2020	J	`jnl`	Neural Networks with Recurrent Generative Feedback. CoRR Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan M. Nguyen, Doris Y. Tsao, Anima Anandkumar
2019	J	`jnl`	Out-of-Distribution Detection Using Neural Rendering Generative Models. CoRR Yujia Huang, Sihui Dai, Tan M. Nguyen, Richard G. Baraniuk, Anima Anandkumar