Chirag Agarwal

88 papers A* 13A 5B 6C 1Journal 50Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning. CoRR Eric Onyame, Akash Ghosh, Subhadip Baidya, Sriparna Saha, Xiuying Chen, Chirag Agarwal
2026	A	`conf`	Improving Human Verification of LLM Reasoning through Interactive Explanation Interfaces. IUI Runtao Zhou, Giang Nguyen, Nikita Kharya, Anh Nguyen, Chirag Agarwal
2026	A*	`conf`	Polarity-Aware Probing for Quantifying Latent Alignment in Language Models. AAAI Sabrina Sadiekh, Elena Ericheva, Chirag Agarwal
2026	J	`jnl`	Quantifying Explanation Quality in Graph Neural Networks using Out-of-Distribution Generalization. CoRR Ding Zhang, Siddharth Betala, Chirag Agarwal
2026	J	`jnl`	STRUCTUREDAGENT: Planning with AND/OR Trees for Long-Horizon Web Tasks. CoRR Elita A. Lobo, Xu Chen, Jingjing Meng, Nan Xi, Yang Jiao, Chirag Agarwal, Yair Zick, Yan Gao
2026	J	`jnl`	Toward Understanding Unlearning Difficulty: A Mechanistic Perspective and Circuit-Guided Difficulty Metric. CoRR Jiali Cheng, Ziheng Chen, Chirag Agarwal, Hadi Amiri
2026	A*	`conf`	Towards Trustworthy Multimodal AI Systems. AAAI Chirag Agarwal
2025	J	`jnl`	A Graph Talks, But Who's Listening? Rethinking Evaluations for Graph-Language Models. CoRR Soham Petkar, Hari Aakash K, Anirudh Vempati, Akshit Sinha, Ponnurangam Kumarauguru, Chirag Agarwal
2025	—	`conf`	A Survey of Multilingual Reasoning in Language Models. EMNLP (Findings) Akash Ghosh, Debayan Datta, Sriparna Saha, Chirag Agarwal
2025	—	`conf`	Analyzing Memorization in Large Language Models through the Lens of Model Attribution. NAACL (Long Papers) Tarun Ram Menta, Susmit Agrawal, Chirag Agarwal
2025	J	`jnl`	Analyzing Memorization in Large Language Models through the Lens of Model Attribution. CoRR Tarun Ram Menta, Susmit Agrawal, Chirag Agarwal
2025	J	`jnl`	CLINIC: Evaluating Multilingual Trustworthiness in Language Models for Healthcare. CoRR Akash Ghosh, Srivarshinee Sridhar, Raghav Kaushik Ravi, Muhsin Muhsin, Sriparna Saha, Chirag Agarwal
2025	J	`jnl`	Do Students Debias Like Teachers? On the Distillability of Bias Mitigation Methods. CoRR Jiali Cheng, Chirag Agarwal, Hadi Amiri
2025	A*	`conf`	EGOILLUSION: Benchmarking Hallucinations in Egocentric Video Understanding. EMNLP Ashish Seth, Utkarsh Tyagi, Ramaneswaran Selvakumar, Nishit Anand, Sonal Kumar, Sreyan Ghosh, Ramani Duraiswami, Chirag Agarwal, Dinesh Manocha
2025	J	`jnl`	EGOILLUSION: Benchmarking Hallucinations in Egocentric Video Understanding. CoRR Ashish Seth, Utkarsh Tyagi, Ramaneswaran Selvakumar, Nishit Anand, Sonal Kumar, Sreyan Ghosh, Ramani Duraiswami, Chirag Agarwal, Dinesh Manocha
2025	J	`jnl`	Improving Human Verification of LLM Reasoning through Interactive Explanation Interfaces. CoRR Runtao Zhou, Giang Nguyen, Nikita Kharya, Anh Totti Nguyen, Chirag Agarwal
2025	J	`jnl`	Interpretable Neuropsychiatric Diagnosis via Concept-Guided Graph Neural Networks. CoRR Song Wang, Zhenyu Lei, Zhen Tan, Jundong Li, Javier Rasero, Aiying Zhang, Chirag Agarwal
2025	—	`conf`	On the Impact of Fine-Tuning on Chain-of-Thought Reasoning. NAACL (Long Papers) Elita A. Lobo, Chirag Agarwal, Himabindu Lakkaraju
2025	J	`jnl`	Polarity-Aware Probing for Quantifying Latent Alignment in Language Models. CoRR Sabrina Sadiekh, Elena Ericheva, Chirag Agarwal
2025	J	`jnl`	Rethinking Explainability in the Era of Multimodal AI. CoRR Chirag Agarwal
2025	J	`jnl`	The Multilingual Mind : A Survey of Multilingual Reasoning in Language Models. CoRR Akash Ghosh, Debayan Datta, Sriparna Saha, Chirag Agarwal
2025	—	`conf`	Towards Operationalizing Right to Data Protection. NAACL (Long Papers) Abhinav Java, Simra Shahid, Chirag Agarwal
2024	—	`conf`	Active Transferability Estimation. CVPR Workshops Tarun Ram Menta, Surgan Jandial, Akash Patil, Saketh Bachu, Vimal K. B., Balaji Krishnamurthy, Vineeth N. Balasubramanian, Mausoom Sarkar, Chirag Agarwal
2024	J	`jnl`	Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Models. CoRR Chirag Agarwal, Sree Harsha Tanneru, Himabindu Lakkaraju
2024	J	`jnl`	HALLUCINOGEN: A Benchmark for Evaluating Object Hallucination in Large Visual-Language Models. CoRR Ashish Seth, Dinesh Manocha, Chirag Agarwal
2024	A*	`conf`	MedSafetyBench: Evaluating and Improving the Medical Safety of Large Language Models. NeurIPS Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju
2024	J	`jnl`	On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models. CoRR Sree Harsha Tanneru, Dan Ley, Chirag Agarwal, Himabindu Lakkaraju
2024	J	`jnl`	On the Impact of Fine-Tuning on Chain-of-Thought Reasoning. CoRR Elita A. Lobo, Chirag Agarwal, Himabindu Lakkaraju
2024	—	`conf`	On the Trade-offs between Adversarial Robustness and Actionable Explanations. AIES (1) Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
2024	A	`conf`	Quantifying Uncertainty in Natural Language Explanations of Large Language Models. AISTATS Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju
2024	J	`jnl`	Towards Operationalizing Right to Data Protection. CoRR Abhinav Java, Simra Shahid, Chirag Agarwal
2024	J	`jnl`	Towards Safe and Aligned Large Language Models for Medicine. CoRR Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju
2024	A*	`conf`	Understanding the Effects of Iterative Prompting on Truthfulness. ICML Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
2024	J	`jnl`	Understanding the Effects of Iterative Prompting on Truthfulness. CoRR Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
2023	J	`jnl`	Are Large Language Models Post Hoc Explainers? CoRR Nicholas Kroeger, Dan Ley, Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
2023	J	`jnl`	Certifying LLM Safety against Adversarial Prompting. CoRR Aounon Kumar, Chirag Agarwal, Suraj Srinivas, Soheil Feizi, Hima Lakkaraju
2023	J	`jnl`	Counterfactual Explanation Policies in RL. CoRR Shripad Vilasrao Deshmukh, Srivatsan R, Supriti Vijay, Jayakumar Subramanian, Chirag Agarwal
2023	A*	`conf`	DeAR: Debiasing Vision-Language Models with Additive Residuals. CVPR Ashish Seth, Mayur Hemani, Chirag Agarwal
2023	J	`jnl`	DeAR: Debiasing Vision-Language Models with Additive Residuals. CoRR Ashish Seth, Mayur Hemani, Chirag Agarwal
2023	A*	`conf`	Explain Like I am BM25: Interpreting a Dense Model's Ranked-List with a Sparse Approximation. SIGIR Michael Llordes, Debasis Ganguly, Sumit Bhatia, Chirag Agarwal
2023	J	`jnl`	Explain like I am BM25: Interpreting a Dense Model's Ranked-List with a Sparse Approximation. CoRR Michael Llordes, Debasis Ganguly, Sumit Bhatia, Chirag Agarwal
2023	A*	`conf`	Explaining RL Decisions with Trajectories. ICLR Shripad Vilasrao Deshmukh, Arpan Dasgupta, Balaji Krishnamurthy, Nan Jiang, Chirag Agarwal, Georgios Theocharous, Jayakumar Subramanian
2023	J	`jnl`	Explaining RL Decisions with Trajectories. CoRR Shripad Vilasrao Deshmukh, Arpan Dasgupta, Balaji Krishnamurthy, Nan Jiang, Chirag Agarwal, Georgios Theocharous, Jayakumar Subramanian
2023	A*	`conf`	GNNDelete: A General Strategy for Unlearning in Graph Neural Networks. ICLR Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik
2023	J	`jnl`	GNNDelete: A General Strategy for Unlearning in Graph Neural Networks. CoRR Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik
2023	J	`jnl`	On the Trade-offs between Adversarial Robustness and Actionable Explanations. CoRR Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
2023	J	`jnl`	Quantifying Uncertainty in Natural Language Explanations of Large Language Models. CoRR Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju
2023	J	`jnl`	Towards Estimating Transferability using Hard Subsets. CoRR Tarun Ram Menta, Surgan Jandial, Akash Patil, Vimal KB, Saketh Bachu, Balaji Krishnamurthy, Vineeth N. Balasubramanian, Chirag Agarwal, Mausoom Sarkar
2022	A*	`conf`	Estimating Example Difficulty using Variance of Gradients. CVPR Chirag Agarwal, Daniel D'souza, Sara Hooker
2022	J	`jnl`	Evaluating Explainability for Graph Neural Networks. CoRR Chirag Agarwal, Owen Queen, Himabindu Lakkaraju, Marinka Zitnik
2022	A	`conf`	Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis. AISTATS Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju
2022	A*	`conf`	OpenXAI: Towards a Transparent Evaluation of Model Explanations. NeurIPS Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju
2022	J	`jnl`	OpenXAI: Towards a Transparent Evaluation of Model Explanations. CoRR Chirag Agarwal, Eshika Saxena, Satyapriya Krishna, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju
2022	A	`conf`	Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods. AISTATS Chirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju
2022	J	`jnl`	Rethinking Stability for Attribution-based Explanations. CoRR Chirag Agarwal, Nari Johnson, Martin Pawelczyk, Satyapriya Krishna, Eshika Saxena, Marinka Zitnik, Himabindu Lakkaraju
2022	—	`conf`	Towards Training GNNs Using Explanation Directed Message Passing. LoG Valentina Giunchiglia, Chirag Varun Shukla, Guadalupe Gonzalez, Chirag Agarwal
2022	J	`jnl`	Towards Training GNNs using Explanation Directed Message Passing. CoRR Valentina Giunchiglia, Chirag Varun Shukla, Guadalupe Gonzalez, Chirag Agarwal
2021	J	`jnl`	A Tale Of Two Long Tails. CoRR Daniel D'souza, Zach Nussbaum, Chirag Agarwal, Sara Hooker
2021	—	`conf`	CoroNet: a deep network architecture for enhanced identification of COVID-19 from chest x-ray images. Computer-Aided Diagnosis Chirag Agarwal, Shahin Khobahi, Dan Schonfeld, Mojtaba Soltanalian
2021	J	`jnl`	On the Connections between Counterfactual Explanations and Adversarial Examples. CoRR Martin Pawelczyk, Shalmali Joshi, Chirag Agarwal, Sohini Upadhyay, Himabindu Lakkaraju
2021	J	`jnl`	Towards a Rigorous Theoretical Analysis and Evaluation of GNN Explanations. CoRR Chirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju
2021	J	`jnl`	Towards a Unified Framework for Fair and Stable Graph Representation Learning. CoRR Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik
2021	A	`conf`	Towards a unified framework for fair and stable graph representation learning. UAI Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik
2021	A*	`conf`	Towards the Unification and Robustness of Perturbation and Gradient Based Explanations. ICML Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Himabindu Lakkaraju
2021	J	`jnl`	Towards the Unification and Robustness of Perturbation and Gradient Based Explanations. CoRR Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Zhiwei Steven Wu, Himabindu Lakkaraju
2020	B	`conf`	DEEP-URL: A Model-Aware Approach to Blind Deconvolution Based on Deep Unfolded Richardson-Lucy Network. ICIP Chirag Agarwal, Shahin Khobahi, Arindam Bose, Mojtaba Soltanalian, Dan Schonfeld
2020	J	`jnl`	Deep-URL: A Model-Aware Approach To Blind Deconvolution Based On Deep Unfolded Richardson-Lucy Network. CoRR Chirag Agarwal, Shahin Khobahi, Arindam Bose, Mojtaba Soltanalian, Dan Schonfeld
2020	J	`jnl`	Estimating Example Difficulty using Variance of Gradients. CoRR Chirag Agarwal, Sara Hooker
2020	—	`conf`	Explaining Image Classifiers by Removing Input Features Using Generative Models. ACCV (6) Chirag Agarwal, Anh Nguyen
2020	J	`jnl`	Intriguing generalization and simplicity of adversarially trained neural networks. CoRR Chirag Agarwal, Peijie Chen, Anh Nguyen
2020	—	`conf`	SAM: The Sensitivity of Attribution Methods to Hyperparameters. CVPR Workshops Naman Bansal, Chirag Agarwal, Anh Nguyen
2020	A*	`conf`	SAM: The Sensitivity of Attribution Methods to Hyperparameters. CVPR Naman Bansal, Chirag Agarwal, Anh Nguyen
2020	J	`jnl`	SAM: The Sensitivity of Attribution Methods to Hyperparameters. CoRR Naman Bansal, Chirag Agarwal, Anh Nguyen
2019	B	`conf`	Improving Robustness to Adversarial Examples by Encouraging Discriminative Features. ICIP Chirag Agarwal, Anh Nguyen, Dan Schonfeld
2019	J	`jnl`	Removing input features via a generative model to explain their attributions to classifier's decisions. CoRR Chirag Agarwal, Dan Schonfeld, Anh Nguyen
2019	—	`conf`	Statistical Sequential Analysis for Object-based Video Forgery Detection. Media Watermarking, Security, and Forensics Mohammed Aloraini, Mehdi Sharifzadeh, Chirag Agarwal, Dan Schonfeld
2018	J	`jnl`	An Explainable Adversarial Robustness Metric for Deep Learning Neural Networks. CoRR Chirag Agarwal, Bo Dong, Dan Schonfeld, Anthony Hoogs
2018	—	`conf`	CrossEncoders: A complex neural network compression framework. Visual Information Processing and Communication Chirag Agarwal, Mehdi Sharifzadeh, Dan Schonfeld
2018	J	`jnl`	Improving Adversarial Robustness by Encouraging Discriminative Features. CoRR Chirag Agarwal, Anh Nguyen, Dan Schonfeld
2018	B	`conf`	Multi-class segmentation of neuronal electron microscopy images using deep learning. Image Processing Nivedita Khobragade, Chirag Agarwal
2017	J	`jnl`	A New Parallel Message-distribution Technique for Cost-based Steganography. CoRR Mehdi Sharifzadeh, Chirag Agarwal, Mahdi Salarian, Dan Schonfeld
2017	B	`conf`	Accurate segmentation of lung fields on chest radiographs using deep convolutional networks. Image Processing Mohammad R. Arbabshirani, Ahmed H. Dallal, Chirag Agarwal, Aalpen Patel, Gregory J. Moore
2017	—	`conf`	Automatic estimation of heart boundaries and cardiothoracic ratio from chest x-ray images. Computer-Aided Diagnosis Ahmed H. Dallal, Chirag Agarwal, Mohammad R. Arbabshirani, Aalpen Patel, Gregory J. Moore
2017	J	`jnl`	Convolutional Neural Network Steganalysis's Application to Steganography. CoRR Mehdi Sharifzadeh, Chirag Agarwal, Mohammed Aloraini, Dan Schonfeld
2017	C	`conf`	Convolutional neural network steganalysis's application to steganography. VCIP Mehdi Sharifzadeh, Chirag Agarwal, Mohammed Aloraini, Dan Schonfeld
2017	J	`jnl`	CrossNets : A New Approach to Complex Learning. CoRR Chirag Agarwal, Mehdi Sharifzadeh, Joe Klobusicky, Dan Schonfeld
2017	B	`conf`	Unsupervised quantification of abdominal fat from CT images using Greedy Snakes. Image Processing Chirag Agarwal, Ahmed H. Dallal, Mohammad R. Arbabshirani, Aalpen Patel, Gregory J. Moore
2015	B	`conf`	Compositional Reasoning Gotchas in Practice. FMCAD Chirag Agarwal, Paul Hylander, Yogesh Mahajan, Jonathan Michelson, Vigyan Singhal