Out-of-Distribution Detection Using Neural Rendering Generative Models. - Yujia Huang; Sihui Dai; Tan M. Nguyen; Richard G. Baraniuk; Anima Anandkumar (CoRR, 2019)

Neural Networks with Recurrent Generative Feedback. - Yujia Huang; James Gornet; Sihui Dai; Zhiding Yu; Tan M. Nguyen; Doris Y. Tsao; Anima Anandkumar (NeurIPS, 2020)

Improving Adversarial Robustness Using Proxy Distributions. - Vikash Sehwag; Saeed Mahloujifar; Tinashe Handina; Sihui Dai; Chong Xiang 001; Mung Chiang; Prateek Mittal (CoRR, 2021)

Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? - Vikash Sehwag; Saeed Mahloujifar; Tinashe Handina; Sihui Dai; Chong Xiang 001; Mung Chiang; Prateek Mittal (ICLR, 2022)

Formulating Robustness Against Unforeseen Attacks. - Sihui Dai; Saeed Mahloujifar; Prateek Mittal (NeurIPS, 2022)

Parameterizing Activation Functions for Adversarial Robustness. - Sihui Dai; Saeed Mahloujifar; Prateek Mittal (SP (Workshops), 2022)

MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. - Sihui Dai; Saeed Mahloujifar; Chong Xiang 001; Vikash Sehwag; Pin-Yu Chen; Prateek Mittal (ICML, 2023)

Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker. - Sihui Dai; Wenxin Ding; Arjun Nitin Bhagoji; Daniel Cullina; Heather Zheng; Ben Zhao; Prateek Mittal (NeurIPS, 2023)

Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker. - Sihui Dai; Wenxin Ding; Arjun Nitin Bhagoji; Daniel Cullina; Ben Y. Zhao; Haitao Zheng 001; Prateek Mittal (CoRR, 2023)

Larimar: Large Language Models with Episodic Memory Control. - Payel Das; Subhajit Chaudhury; Elliot Nelson; Igor Melnyk; Sarathkrishna Swaminathan; Sihui Dai; Aurélie C. Lozano; Georgios Kollias; Vijil Chenthamarakshan; Jirí Navrátil 001; Soham Dan; Pin-Yu Chen (ICML, 2024)

PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses. - Chong Xiang 001; Tong Wu; Sihui Dai; Jonathan Petit; Suman Jana; Prateek Mittal (USENIX Security Symposium, 2024)

Larimar: Large Language Models with Episodic Memory Control. - Payel Das; Subhajit Chaudhury; Elliot Nelson; Igor Melnyk; Sarath Swaminathan; Sihui Dai; Aurélie C. Lozano; Georgios Kollias; Vijil Chenthamarakshan; Jirí Navrátil 001; Soham Dan; Pin-Yu Chen (CoRR, 2024)

Position Paper: Beyond Robustness Against Single Attack Types. - Sihui Dai; Chong Xiang 001; Tong Wu; Prateek Mittal (CoRR, 2024)

Adapting to Evolving Adversaries with Regularized Continual Robust Training. - Sihui Dai; Christian Cianfarani; Arjun Nitin Bhagoji; Vikash Sehwag; Prateek Mittal (CoRR, 2025)

Can Memory-Augmented Language Models Generalize on Reasoning-in-a-Haystack Tasks? - Payel Das; Ching-Yun Ko; Sihui Dai; Georgios Kollias; Subhajit Chaudhury; Aurélie C. Lozano (CoRR, 2025)