Capacitated k-Center Problem with Vertex Weights. - Aounon Kumar (FSTTCS, 2016)

On the Cost of Essentially Fair Clusterings. - Ioana Oriana Bercea; Martin Groß 001; Samir Khuller; Aounon Kumar; Clemens Rösner; Daniel R. Schmidt 001; Melanie Schmidt 001 (APPROX-RANDOM, 2019)

Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness. - Aounon Kumar; Alexander Levine 001; Tom Goldstein; Soheil Feizi (ICML, 2020)

Detection as Regression: Certified Object Detection with Median Smoothing. - Ping-yeh Chiang; Michael J. Curry; Ahmed Abdelkader; Aounon Kumar; John Dickerson 001; Tom Goldstein (NeurIPS, 2020)

Certifying Confidence via Randomized Smoothing. - Aounon Kumar; Alexander Levine 001; Soheil Feizi; Tom Goldstein (NeurIPS, 2020)

Detection as Regression: Certified Object Detection by Median Smoothing. - Ping-yeh Chiang; Michael J. Curry; Ahmed Abdelkader; Aounon Kumar; John P. Dickerson; Tom Goldstein (CoRR, 2020)

Tight Second-Order Certificates for Randomized Smoothing. - Alexander Levine 001; Aounon Kumar; Thomas A. Goldstein; Soheil Feizi (CoRR, 2020)

Center Smoothing: Certified Robustness for Networks with Structured Outputs. - Aounon Kumar; Tom Goldstein (NeurIPS, 2021)

Center Smoothing for Certifiably Robust Vector-Valued Functions. - Aounon Kumar; Tom Goldstein (CoRR, 2021)

Policy Smoothing for Provably Robust Reinforcement Learning. - Aounon Kumar; Alexander Levine 001; Soheil Feizi (ICLR, 2022)

Certifying Model Accuracy under Distribution Shifts. - Aounon Kumar; Alexander Levine 001; Tom Goldstein; Soheil Feizi (CoRR, 2022)

Provable Robustness against Wasserstein Distribution Shifts via Input Randomization. - Aounon Kumar; Alexander Levine 001; Tom Goldstein; Soheil Feizi (ICLR, 2023)

Can AI-Generated Text be Reliably Detected? - Vinu Sankar Sadasivan; Aounon Kumar; Sriram Balasubramanian; Wenxiao Wang 002; Soheil Feizi (CoRR, 2023)

Provable Robustness for Streaming Models with a Sliding Window. - Aounon Kumar; Vinu Sankar Sadasivan; Soheil Feizi (CoRR, 2023)

Certifying LLM Safety against Adversarial Prompting. - Aounon Kumar; Chirag Agarwal; Suraj Srinivas; Soheil Feizi; Hima Lakkaraju (CoRR, 2023)

Extending the Scope of Provable Adversarial Robustness in Machine Learning. - Aounon Kumar (2023)

Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks. - Mehrdad Saberi; Vinu Sankar Sadasivan; Keivan Rezaei; Aounon Kumar; Atoosa Malemir Chegini; Wenxiao Wang 002; Soheil Feizi (ICLR, 2024)

MedSafetyBench: Evaluating and Improving the Medical Safety of Large Language Models. - Tessa Han; Aounon Kumar; Chirag Agarwal; Himabindu Lakkaraju (NeurIPS, 2024)

Towards Safe and Aligned Large Language Models for Medicine. - Tessa Han; Aounon Kumar; Chirag Agarwal; Himabindu Lakkaraju (CoRR, 2024)

Manipulating Large Language Models to Increase Product Visibility. - Aounon Kumar; Himabindu Lakkaraju (CoRR, 2024)

Can AI-Generated Text be Reliably Detected? Stress Testing AI Text Detectors Under Various Attacks. - Vinu Sankar Sadasivan; Aounon Kumar; Sriram Balasubramanian; Wenxiao Wang 002; Soheil Feizi (Trans. Mach. Learn. Res., 2025)

Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models. - Martin Pawelczyk; Lillian Sun; Zhenting Qi; Aounon Kumar; Himabindu Lakkaraju (CoRR, 2025)

Detecting LLM-Written Peer Reviews. - Vishisht Rao; Aounon Kumar; Himabindu Lakkaraju; Nihar B. Shah (CoRR, 2025)