Sihui Dai

According to our database, Sihui Dai authored at least 17 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Decomposing the Delta: What Do Models Actually Learn from Preference Pairs?

Chia-Hsuan Lee, Mingyang Zhou, Renkun Ni, Zelei Cheng, Sihui Dai, Supriyo Chakraborty, Shixiong Zhang, Sambit Sahu, William Campbell

CoRR, April, 2026

ImReasoner: Improving Memory-based Language Models for Reasoning-in-a-Haystack Tasks.

Ching-Yun Ko, Payel Das, Sihui Dai, Georgios Kollias, Subhajit Chaudhury, Aurélie C. Lozano, Pin-Yu Chen

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

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, March, 2025

Adapting to Evolving Adversaries with Regularized Continual Robust Training.

Sihui Dai, Christian Cianfarani, Vikash Sehwag, Prateek Mittal, Arjun Nitin Bhagoji

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Position Paper: Beyond Robustness Against Single Attack Types.

Sihui Dai, Chong Xiang, Tong Wu, Prateek Mittal

CoRR, 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, Soham Dan, Pin-Yu Chen

CoRR, 2024

PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses.

Chong Xiang, Tong Wu, Sihui Dai, Jonathan Petit, Suman Jana, Prateek Mittal

Proceedings of the 33rd USENIX Security Symposium, 2024

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, Soham Dan, Pin-Yu Chen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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, Prateek Mittal

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MultiRobustBench: Benchmarking Robustness Against Multiple Attacks.

Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal

Proceedings of the International Conference on Machine Learning, 2023

2022

Parameterizing Activation Functions for Adversarial Robustness.

Sihui Dai, Saeed Mahloujifar, Prateek Mittal

Proceedings of the 43rd IEEE Security and Privacy, 2022

Formulating Robustness Against Unforeseen Attacks.

Sihui Dai, Saeed Mahloujifar, Prateek Mittal

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?

Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Improving Adversarial Robustness Using Proxy Distributions.

Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal

CoRR, 2021

2020

Neural Networks with Recurrent Generative Feedback.

Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan M. Nguyen, Doris Y. Tsao, Anima Anandkumar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Out-of-Distribution Detection Using Neural Rendering Generative Models.

Yujia Huang, Sihui Dai, Tan M. Nguyen, Richard G. Baraniuk, Anima Anandkumar

CoRR, 2019