Agarwal, Chirag

29 publications

ICLRW 2025 Analyzing Memorization in Large Language Models Through the Lens of Model Attribution Tarun Ram Menta, Susmit Agrawal, Chirag Agarwal

ICLRW 2025 Towards Operationalizing Right to Data Protection Simra Shahid, Abhinav Java, Chirag Agarwal

CVPRW 2024 Active Transferability Estimation Tarun Ram Menta, Surgan Jandial, Akash Patil, Saketh Bachu, K. B. Vimal, Balaji Krishnamurthy, Vineeth N. Balasubramanian, Mausoom Sarkar, Chirag Agarwal

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

ICMLW 2024 On the Difficulty of Faithful Chain-of-Thought Reasoning in Large Language Models Sree Harsha Tanneru, Dan Ley, Chirag Agarwal, Himabindu Lakkaraju

AISTATS 2024 Quantifying Uncertainty in Natural Language Explanations of Large Language Models Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju

ICMLW 2024 Towards Safe Large Language Models for Medicine Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

ICMLW 2024 Towards Safe Large Language Models for Medicine Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

ICMLW 2024 Towards Safe Large Language Models for Medicine Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

ICML 2024 Understanding the Effects of Iterative Prompting on Truthfulness Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju

NeurIPSW 2023 Are Large Language Models Post Hoc Explainers? Nicholas Kroeger, Dan Ley, Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju

NeurIPSW 2023 Are Large Language Models Post Hoc Explainers? Nicholas Kroeger, Dan Ley, Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju

CVPR 2023 DeAR: Debiasing Vision-Language Models with Additive Residuals Ashish Seth, Mayur Hemani, Chirag Agarwal

ICLR 2023 Explaining RL Decisions with Trajectories Shripad Vilasrao Deshmukh, Arpan Dasgupta, Balaji Krishnamurthy, Nan Jiang, Chirag Agarwal, Georgios Theocharous, Jayakumar Subramanian

ICLR 2023 GNNDelete: A General Strategy for Unlearning in Graph Neural Networks Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik

ICLRW 2023 Intriguing Properties of Visual-Language Model Explanations Chirag Agarwal

NeurIPSW 2023 Quantifying Uncertainty in Natural Language Explanations of Large Language Models Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju

ICMLW 2023 Towards Fair Knowledge Distillation Using Student Feedback Abhinav Java, Surgan Jandial, Chirag Agarwal

AISTATS 2022 Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju

AISTATS 2022 Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju

CVPR 2022 Estimating Example Difficulty Using Variance of Gradients Chirag Agarwal, Daniel D'souza, Sara Hooker

NeurIPSW 2022 On the Impact of Adversarially Robust Models on Algorithmic Recourse Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju

NeurIPS 2022 OpenXAI: Towards a Transparent Evaluation of Model Explanations Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju

ICLRW 2022 Rethinking Stability for Attribution-Based Explanations Chirag Agarwal, Nari Johnson, Martin Pawelczyk, Satyapriya Krishna, Eshika Saxena, Marinka Zitnik, Himabindu Lakkaraju

LoG 2022 Towards Training GNNs Using Explanation Directed Message Passing Valentina Giunchiglia, Chirag Varun Shukla, Guadalupe Gonzalez, Chirag Agarwal

NeurIPSW 2022 Trajectory-Based Explainability Framework for Offline RL Shripad Vilasrao Deshmukh, Arpan Dasgupta, Chirag Agarwal, Nan Jiang, Balaji Krishnamurthy, Georgios Theocharous, Jayakumar Subramanian

UAI 2021 Towards a Unified Framework for Fair and Stable Graph Representation Learning Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik

ICML 2021 Towards the Unification and Robustness of Perturbation and Gradient Based Explanations Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Himabindu Lakkaraju

CVPRW 2020 SAM: The Sensitivity of Attribution Methods to Hyperparameters Naman Bansal, Chirag Agarwal, Anh Nguyen