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Himabindu Lakkaraju

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Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems

Feb 27, 2024
Zhenting Qi, Hanlin Zhang, Eric Xing, Sham Kakade, Himabindu Lakkaraju

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Opening the Black Box of Large Language Models: Two Views on Holistic Interpretability

Feb 16, 2024
Haiyan Zhao, Fan Yang, Himabindu Lakkaraju, Mengnan Du

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Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)

Feb 16, 2024
Usha Bhalla, Alex Oesterling, Suraj Srinivas, Flavio P. Calmon, Himabindu Lakkaraju

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Understanding the Effects of Iterative Prompting on Truthfulness

Feb 09, 2024
Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju

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

Feb 08, 2024
Chirag Agarwal, Sree Harsha Tanneru, Himabindu Lakkaraju

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Quantifying Uncertainty in Natural Language Explanations of Large Language Models

Nov 06, 2023
Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju

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Investigating the Fairness of Large Language Models for Predictions on Tabular Data

Oct 23, 2023
Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju

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In-Context Unlearning: Language Models as Few Shot Unlearners

Oct 12, 2023
Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju

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Are Large Language Models Post Hoc Explainers?

Oct 10, 2023
Nicholas Kroeger, Dan Ley, Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju

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