← Authors

Somesh Jha

38 papers · 2018–2025 · 9 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (7) 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (9) πŸ—ΊοΈ Taxonomy Completionist (35) 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (11) πŸ”₯ Unstoppable (8) πŸ’Ž Century Club (38) πŸ—ƒοΈ Keyword Collector (95) ❓ The Questioner (2) ⚑ Prolific Year (5)

Conferences

ICML (12) ICLR (11) NIPS (9) ACL (1) AISTATS (1) ALT (1) EMNLP (1) MLHC (1) WACV (1)

Top co-authors

Jiefeng Chen (10) Xi Wu (8) Yingyu Liang (6) Jayaram Raghuram (6) Jihye Choi (5) Ashish Hooda (4) Atul Prakash (3) Kamalika Chaudhuri (3) Sanjam Garg (3) Nils Palumbo (3)

Research topics

Privacy (1)

Keywords

adversarial robustness (7) adversarial training (4) adversarial learning (3) neural network (3) deep neural network (2) attribution method (2) out-of-distribution detection (2) robust classification (2) learning theory (2) large language model (2) adversarial attack (2) integrated gradient (2) symbolic reasoning (1) uncertainty quantification (1) robust optimization (1) feature selection (1) ensemble learning (1) differential privacy (1) anomaly detection (1) neural network interpretability (1)

Papers

On the Difficulty of Constructing a Robust and Publicly-Detectable Watermark AISTATS 2025
Validating Mechanistic Interpretations: An Axiomatic Approach ICML 2025
Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks ICLR 2025
CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts ICLR 2025
AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs ICLR 2025
Can Watermarks be Used to Detect LLM IP Infringement For Free? ICLR 2025
D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles WACV 2024
PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails ACL 2024
On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks ICLR 2024
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates ICML 2024
Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection ICML 2024
MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance MLHC 2024
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs EMNLP 2023
Robust and Actively Secure Serverless Collaborative Learning NIPS 2023
Stratified Adversarial Robustness with Rejection ICML 2023
Concept-based Explanations for Out-of-Distribution Detectors ICML 2023
Grounding Neural Inference with Satisfiability Modulo Theories NIPS 2023
Few-Shot Domain Adaptation For End-to-End Communication ICLR 2023
The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning ICLR 2023
Privacy Implications of Shuffling ICLR 2022
Robust Learning against Relational Adversaries NIPS 2022
Overparameterization from Computational Constraints NIPS 2022
A Quantitative Geometric Approach to Neural-Network Smoothness NIPS 2022
Towards Evaluating the Robustness of Neural Networks Learned by Transduction ICLR 2022
Sample Complexity of Robust Linear Classification on Separated Data ICML 2021
A General Framework For Detecting Anomalous Inputs to DNN Classifiers ICML 2021
CaPC Learning: Confidential and Private Collaborative Learning ICLR 2021
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles NIPS 2021
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks NIPS 2021
Adversarially Robust Learning Could Leverage Computational Hardness. ALT 2020
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses ICLR 2020
Concise Explanations of Neural Networks using Adversarial Training ICML 2020
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models ICML 2020
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods ICML 2020
Attribution-Based Confidence Metric For Deep Neural Networks NIPS 2019
Robust Attribution Regularization NIPS 2019
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training ICML 2018
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples ICML 2018