Stengel-Eskin, Elias

GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations

Duan, J., Zhang, R., Diffenderfer, J., Kailkhura, B., Sun, L., Stengel-Eskin, E., Bansal, M., Chen, T., & Xu, K. (2024) · Advances in Neural Information Processing Systems 37

Artificial Intelligence in GamesGame Theory and Applications

Cited by 39

MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning

Chen, J., Prasad, A., Saha, S., Stengel-Eskin, E., & Bansal, M. (2025) · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 38

GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations

Duan, J., Zhang, R., Diffenderfer, J., Kailkhura, B., Sun, L., Stengel-Eskin, E., Bansal, M., Chen, T., & Xu, K. (2024) · arXiv

Artificial Intelligence in GamesTopic Modeling

Cited by 4

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

ReGAL: Refactoring Programs to Discover Generalizable Abstractions

Stengel-Eskin, E., Prasad, A., & Bansal, M. (2024) · arXiv

Software Engineering ResearchTeaching and Learning Programming

Cited by 1

Who is the Agent to Blame? Localizing Faithfulness and Citation Mistakes in Agentic Deep Research

Hirsch, E., Wan, D., Wang, H., Stengel-Eskin, E., Bansal, M., & Dagan, I. (2026) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0

GenerationPrograms: Fine-grained Attribution with Executable Programs

Wan, D., Hirsch, E., Stengel-Eskin, E., Dagan, I., & Bansal, M. (2025) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 0