Rytting, Christopher

Out of One, Many: Using Language Models to Simulate Human Samples

Argyle, L. P., Busby, E. C., Fulda, N., Gubler, J. R., Rytting, C., & Wingate, D. (2023) · Political Analysis

Ethics and Social Impacts of AIComputational and Text Analysis Methods

Cited by 783

Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces

Merrill, M. A., Shaw, A. G., Carlini, N., Li, B., Raj, H., Bercovich, I., Shi, L., Shin, J. Y., Walshe, T., Buchanan, E. K., et al. (2026) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence Applications

Cited by 392

Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale

Argyle, L. P., Bail, C. A., Busby, E. C., Gubler, J. R., Howe, T., Rytting, C., Sorensen, T., & Wingate, D. (2023) · Proceedings of the National Academy of Sciences

Social Media and PoliticsMisinformation and Its Impacts

Cited by 144

An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels

Sorensen, T., Robinson, J., Rytting, C., Shaw, A., Rogers, K., Delorey, A., Khalil, M., Fulda, N., & Wingate, D. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 113

Towards Coding Social Science Datasets with Language Models

Rytting, C. M., Sorensen, T., Argyle, L., Busby, E., Fulda, N., Gubler, J., & Wingate, D. (2023) · arXiv

Computational and Text Analysis MethodsArtificial Intelligence in Law

Cited by 18