Publications

Dan Ley, Shichang Zhang, Suraj Srinivas, Gili Rusak, Himabindu Lakkaraju (2024). Generalized Group Data Attribution. Preprint.

Nicholas Kroeger, Dan Ley, Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju (2024). In-Context Explainers: Harnessing LLMs for Explaining Black Box Models. Preprint.

Sree Harsha Tanneru, Dan Ley, Chirag Agarwal, Himabindu Lakkaraju (2024). On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models. In ICML Workshop on Trustworthy Multi-modal Foundation Models and AI Agents (TiFA).

Anna Meyer, Dan Ley, Suraj Srinivas, Himabindu Lakkaraju (2023). On Minimizing the Impact of Dataset Shifts on Actionable Explanations. In UAI (Oral, Top 5%).

Leonard Tang, Dan Ley (2023). Degraded Polygons Raise Fundamental Questions of Neural Network Perception. In NeurIPS.

Dan Ley, Leonard Tang, Matthew Nazari, Hongjin Lin, Suraj Srinivas, Himabindu Lakkaraju (2023). Consistent Explanations in the Face of Model Indeterminacy via Ensembling. In ICML Workshop on Interpretable Machine Learning in Healthcare.

Dan Ley, Saumitra Mishra, Daniele Magazzeni (2023). GLOBE-CE: A Translation-Based Approach for Global Counterfactual Explanations. In ICML.

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

Dan Ley, Saumitra Mishra, Daniele Magazzeni (2022). Global Counterfactual Explanations: Investigations, Implementations and Improvements. In ICLR Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data.

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Dan Ley, Umang Bhatt, Adrian Weller (2022). Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates. In AAAI.

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