Jha, Somesh

43 publications

ICLR 2025 AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs Xiaogeng Liu, Peiran Li, G. Edward Suh, Yevgeniy Vorobeychik, Zhuoqing Mao, Somesh Jha, Patrick McDaniel, Huan Sun, Bo Li, Chaowei Xiao

ICLR 2025 CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Jihye Choi, Jayaram Raghuram, Yixuan Li, Somesh Jha

ICLR 2025 Can Watermarks Be Used to Detect LLM IP Infringement for Free? Zhengyue Zhao, Xiaogeng Liu, Somesh Jha, Patrick McDaniel, Bo Li, Chaowei Xiao

ICLR 2025 Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks Zi Wang, Divyam Anshumaan, Ashish Hooda, Yudong Chen, Somesh Jha

AISTATS 2025 On the Difficulty of Constructing a Robust and Publicly-Detectable Watermark Jaiden Fairoze, Guillermo Ortiz-Jimenez, Mel Vecerik, Somesh Jha, Sven Gowal

ICML 2025 Validating Mechanistic Interpretations: An Axiomatic Approach Nils Palumbo, Ravi Mangal, Zifan Wang, Saranya Vijayakumar, Corina S. Pasareanu, Somesh Jha

NeurIPS 2025 What Really Is a Member? Discrediting Membership Inference via Poisoning Neal Mangaokar, Ashish Hooda, Zhuohang Li, Bradley A. Malin, Kassem Fawaz, Somesh Jha, Atul Prakash, Amrita Roy Chowdhury

TMLR 2024 ASPEST: Bridging the Gap Between Active Learning and Selective Prediction Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan O Arik, Somesh Jha, Tomas Pfister

ICMLW 2024 Adaptive Concept Bottleneck for Foundation Models Jihye Choi, Jayaram Raghuram, Yixuan Li, Suman Banerjee, Somesh Jha

WACV 2024 D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash

ICML 2024 Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis, Aaron Wilson, Kassem Fawaz, Somesh Jha

MLHC 2024 MALADE: Orchestration of LLM-Powered Agents with Retrieval Augmented Generation for Pharmacovigilance Jihye Choi, Nils Palumbo, Prasad Chalasani, Matthew M. Engelhard, Somesh Jha, Anivarya Kumar, David Page

ICLR 2024 On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks Zi Wang, Bin Hu, Aaron J Havens, Alexandre Araujo, Yang Zheng, Yudong Chen, Somesh Jha

ICML 2024 Two Heads Are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection Nils Palumbo, Yang Guo, Xi Wu, Jiefeng Chen, Yingyu Liang, Somesh Jha

ICML 2023 Concept-Based Explanations for Out-of-Distribution Detectors Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash

ICLR 2023 Few-Shot Domain Adaptation for End-to-End Communication Jayaram Raghuram, Yijing Zeng, Dolores Garcia, Rafael Ruiz, Somesh Jha, Joerg Widmer, Suman Banerjee

NeurIPS 2023 Grounding Neural Inference with Satisfiability Modulo Theories Zifan Wang, Saranya Vijayakumar, Kaiji Lu, Vijay Ganesh, Somesh Jha, Matt Fredrikson

NeurIPS 2023 Robust and Actively Secure Serverless Collaborative Learning Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang

ICML 2023 Stratified Adversarial Robustness with Rejection Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha

ICLR 2023 The Trade-Off Between Universality and Label Efficiency of Representations from Contrastive Learning Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha

ICMLW 2023 Theoretically Principled Trade-Off for Stateful Defenses Against Query-Based Black-Box Attacks Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash

NeurIPS 2022 A Quantitative Geometric Approach to Neural-Network Smoothness Zi Wang, Gautam Prakriya, Somesh Jha

NeurIPSW 2022 Best of Both Worlds: Towards Adversarial Robustness with Transduction and Rejection Nils Palumbo, Xi Wu, Yang Guo, Jiefeng Chen, Yingyu Liang, Somesh Jha

NeurIPS 2022 Overparameterization from Computational Constraints Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang

ICLR 2022 Privacy Implications of Shuffling Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha

NeurIPS 2022 Robust Learning Against Relational Adversaries Yizhen Wang, Mohannad Alhanahnah, Xiaozhu Meng, Ke Wang, Mihai Christodorescu, Somesh Jha

ICMLW 2022 The Trade-Off Between Label Efficiency and Universality of Representations from Contrastive Learning Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha

ICLR 2022 Towards Evaluating the Robustness of Neural Networks Learned by Transduction Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha

ICML 2021 A General Framework for Detecting Anomalous Inputs to DNN Classifiers Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee

NeurIPS 2021 A Separation Result Between Data-Oblivious and Data-Aware Poisoning Attacks Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Guha Thakurta

ECML-PKDD 2021 ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha

ICLR 2021 CaPC Learning: Confidential and Private Collaborative Learning Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang

NeurIPS 2021 Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-Training Ensembles Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha

ICML 2021 Sample Complexity of Robust Linear Classification on Separated Data Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri

ALT 2020 Adversarially Robust Learning Could Leverage Computational Hardness. Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mahmoody Mohammad

ICML 2020 CAUSE: Learning Granger Causality from Event Sequences Using Attribution Methods Wei Zhang, Thomas Panum, Somesh Jha, Prasad Chalasani, David Page

ICML 2020 Concise Explanations of Neural Networks Using Adversarial Training Prasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Xi Wu, Somesh Jha

ICML 2020 Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha

ICLR 2020 On the Need for Topology-Aware Generative Models for Manifold-Based Defenses Uyeong Jang, Susmit Jha, Somesh Jha

NeurIPS 2019 Attribution-Based Confidence Metric for Deep Neural Networks Susmit Jha, Sunny Raj, Steven Fernandes, Sumit K Jha, Somesh Jha, Brian Jalaian, Gunjan Verma, Ananthram Swami

NeurIPS 2019 Robust Attribution Regularization Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha

ICML 2018 Analyzing the Robustness of Nearest Neighbors to Adversarial Examples Yizhen Wang, Somesh Jha, Kamalika Chaudhuri

ICML 2018 Reinforcing Adversarial Robustness Using Model Confidence Induced by Adversarial Training Xi Wu, Uyeong Jang, Jiefeng Chen, Lingjiao Chen, Somesh Jha