Lakkaraju, Himabindu

Human Decisions and Machine Predictions

Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2018) · The Quarterly Journal of Economics

Criminal Justice and Corrections AnalysisArtificial Intelligence in Law

Cited by 1,040

Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods

Slack, D., Hilgard, S., Jia, E., Singh, S., & Lakkaraju, H. (2020) · Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society

Explainable Artificial Intelligence (XAI)Adversarial Robustness in Machine Learning

Cited by 900

Interpretable Decision Sets: A Joint Framework for Description and Prediction

Lakkaraju, H., Bach, S. H., & Leskovec, J. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Explainable Artificial Intelligence (XAI)Data Mining Algorithms and Applications

Cited by 687

Human Decisions and Machine Predictions

Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2017) · National Bureau of Economic Research

Artificial Intelligence in LawCriminal Justice and Corrections Analysis

Cited by 545

"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations

Lakkaraju, H., & Bastani, O. (2020) · Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 241

Evaluating explainability for graph neural networks

Agarwal, C., Queen, O., Lakkaraju, H., & Zitnik, M. (2023) · Scientific Data

Explainable Artificial Intelligence (XAI)Advanced Graph Neural Networks

Cited by 186

The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables

Lakkaraju, H., Kleinberg, J., Leskovec, J., Ludwig, J., & Mullainathan, S. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Advanced Causal Inference TechniquesEthics and Social Impacts of AI

Cited by 138

Explaining machine learning models with interactive natural language conversations using TalkToModel

Slack, D., Krishna, S., Lakkaraju, H., & Singh, S. (2023) · Nature Machine Intelligence

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 125

Rethinking Explainability as a Dialogue: A Practitioner's Perspective

Lakkaraju, H., Slack, D., Chen, Y., Tan, C., & Singh, S. (2022) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 62

“Who, when, and why: a machine learning approach to prioritizing students at risk of not graduating high school on time,”

Aguiar, E., Lakkaraju, H., Bhanpuri, N., Miller, D., Yuhas, B., & Addison, K. L. (2015) · Proceedings of the Fifth International Conference on Learning Analytics And Knowledge

Online Learning and AnalyticsEducational Outcomes and Influences

Cited by 52

Certifying LLM Safety against Adversarial Prompting

Kumar, A., Agarwal, C., Srinivas, S., Li, A. J., Feizi, S., & Lakkaraju, H. (2023) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 28

Interpretable & Explorable Approximations of Black Box Models

Lakkaraju, H., Kamar, E., Caruana, R., & Leskovec, J. (2017) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 23

Interpretability Needs a New Paradigm

Madsen, A., Lakkaraju, H., Reddy, S., & Chandar, S. (2024) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 22

In-Context Unlearning: Language Models as Few Shot Unlearners

Pawelczyk, M., Neel, S., & Lakkaraju, H. (2023) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 20

Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Models

Agarwal, C., Tanneru, S. H., & Lakkaraju, H. (2024) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 14

Detecting LLM-generated peer reviews

Rao, V. S., Kumar, A., Lakkaraju, H., & Shah, N. B. (2025) · PLOS One

Advanced Steganography and Watermarking TechniquesAcademic integrity and plagiarism

Cited by 14

Learning Cost-Effective Treatment Regimes using Markov Decision Processes

Lakkaraju, H., & Rudin, C. (2016) · arXiv

Advanced Causal Inference TechniquesMachine Learning in Healthcare

Cited by 12

How Memory Management Impacts LLM Agents: An Empirical Study of Experience-Following Behavior

Xiong, Z., Lin, Y., Xie, W., He, P., Liu, Z., Tang, J., Lakkaraju, H., & Xiang, Z. (2026) · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 4

How Memory Management Impacts LLM Agents: An Empirical Study of Experience-Following Behavior

Xiong, Z., Lin, Y., Xie, W., He, P., Liu, Z., Tang, J., Lakkaraju, H., & Xiang, Z. (2025) · arXiv

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 3

Post Hoc Explanations of Language Models Can Improve Language Models

Krishna, S., Ma, J., Slack, D., Ghandeharioun, A., Singh, S., & Lakkaraju, H. (2023) · Advances in Neural Information Processing Systems 36

Explainable Artificial Intelligence (XAI)Natural Language Processing Techniques

Cited by 2

Manipulating Large Language Models to Increase Product Visibility

Kumar, A., & Lakkaraju, H. (2024) · arXiv

Information Retrieval and Search BehaviorRecommender Systems and Techniques

Cited by 2

On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Tanneru, S. H., Ley, D., Agarwal, C., & Lakkaraju, H. (2024) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 1