Cohan, Arman

Evaluating LLMs at Detecting Errors in LLM Responses

Kamoi, R., Das, S. S. S., Lou, R., Ahn, J. J., Zhao, Y., Lu, X., Zhang, N., Zhang, Y., Zhang, R. H., Vummanthala, S. R., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 5

PHYSICS: Benchmarking Foundation Models on University-Level Physics Problem Solving

Feng, K., Zhao, Y., Liu, Y., Yang, T., Zhao, C., Sous, J., & Cohan, A. (2025) · arXiv

Topic ModelingEducational Methods and Outcomes

Cited by 3

MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting

Lauscher, A., Ko, B., Kuehl, B., Johnson, S., Jurgens, D., Cohan, A., & Lo, K. (2021) · arXiv

scientometrics and bibliometrics researchTopic Modeling

Cited by 3

MedicalAgentsBench for Complex Medical Reasoning: Comparing Internalized Reasoning Models versus Externalized Agent-based Frameworks

Shao, Y., Tang, X., Sohn, J., Chen, J., Liao, Y., Zhang, J., Xiang, J., Wu, F., Zhao, Y., Wu, C., et al. (2025) · arXiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 3

SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature

Wadden, D., Shi, K., Morrison, J., Li, A., Naik, A., Singh, S., Barzilay, N., Lo, K., Hope, T., Soldaini, L., et al. (2025) · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 3

LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization

Krishna, K., Bransom, E., Kuehl, B., Iyyer, M., Dasigi, P., Cohan, A., & Lo, K. (2023) · arXiv

Topic ModelingAdvanced Text Analysis Techniques

Cited by 3

ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code

Tang, X., Liu, Y., Cai, Z., Shao, Y., Lu, J., Zhang, Y., Deng, Z., Hu, H., An, K., Huang, R., et al. (2023) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 2

FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions

Weller, O., Chang, B., MacAvaney, S., Lo, K., Cohan, A., Van Durme, B., Lawrie, D., & Soldaini, L. (2024) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 1

Bayesian Calibration of Win Rate Estimation with LLM Evaluators

Gao, Y., Xu, G., Wang, Z., & Cohan, A. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 1

AlphaResearch: Accelerating New Algorithm Discovery with Language Models

Yu, Z., Feng, K., Zhao, Y., He, S., Zhang, X.-P., & Cohan, A. (2025) · arXiv

Evolutionary Algorithms and ApplicationsAI-based Problem Solving and Planning

Cited by 0

A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers

Dasigi, P., Lo, K., Beltagy, I., Cohan, A., Smith, N. A., & Gardner, M. (2021) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0

LocAgent: Graph-Guided LLM Agents for Code Localization

Chen, Z., Tang, X., Deng, G., Wu, F., Wu, J., Jiang, Z., Prasanna, V., Cohan, A., & Wang, X. (2025) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 0