Hase, Peter

Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?

Hase, P., & Bansal, M. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 254

GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models

Prasad, A., Hase, P., Zhou, X., & Bansal, M. (2023) · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 78

Leakage-Adjusted Simulatability: Can Models Generate Non-Trivial Explanations of Their Behavior in Natural Language?

Hase, P., Zhang, S., Xie, H., & Bansal, M. (2020) · Findings of the Association for Computational Linguistics: EMNLP 2020

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 62

Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language Models

Hase, P., Bansal, M., Kim, B., & Ghandeharioun, A. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 33

Reasoning Models Don't Always Say What They Think

Chen, Y., Benton, J., Radhakrishnan, A., Uesato, J., Denison, C., Schulman, J., Somani, A., Hase, P., Wagner, M., Roger, F., et al. (2025) · arXiv

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

Cited by 18

Fundamental Problems With Model Editing: How Should Rational Belief Revision Work in LLMs?

Hase, P., Hofweber, T., Zhou, X., Stengel-Eskin, E., & Bansal, M. (2024) · arXiv

Logic, Reasoning, and KnowledgeTopic Modeling

Cited by 1

Unsupervised Elicitation of Language Models

Wen, J., Ankner, Z., Somani, A., Hase, P., Marks, S., Goldman-Wetzler, J., Petrini, L., Sleight, H., Burns, C., He, H., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0