Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning. - Christopher Michael Rytting; David Wingate (NeurIPS, 2021)

An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels. - Taylor Sorensen; Joshua Robinson; Christopher Michael Rytting; Alexander Glenn Shaw; Kyle Jeffrey Rogers; Alexia Pauline Delorey; Mahmoud Khalil; Nancy Fulda; David Wingate (ACL (1), 2022)

Out of One, Many: Using Language Models to Simulate Human Samples. - Lisa P. Argyle; Ethan C. Busby; Nancy Fulda; Joshua Gubler; Christopher Michael Rytting; David Wingate (CoRR, 2022)

Leveraging Large Language Models for Multiple Choice Question Answering. - Joshua Robinson; Christopher Michael Rytting; David Wingate (CoRR, 2022)

AI Chat Assistants can Improve Conversations about Divisive Topics. - Lisa P. Argyle; Ethan C. Busby; Joshua Gubler; Chris Bail; Thomas Vin Howe; Christopher Michael Rytting; David Wingate (CoRR, 2023)

Towards Coding Social Science Datasets with Language Models. - Christopher Michael Rytting; Taylor Sorensen; Lisa P. Argyle; Ethan C. Busby; Nancy Fulda; Joshua Gubler; David Wingate (CoRR, 2023)

IMBUE: Improving Interpersonal Effectiveness through Simulation and Just-in-time Feedback with Human-Language Model Interaction. - Inna W. Lin; Ashish Sharma 004; Christopher Michael Rytting; Adam S. Miner; Jina Suh; Tim Althoff (ACL (1), 2024)

Position: A Roadmap to Pluralistic Alignment. - Taylor Sorensen; Jared Moore; Jillian Fisher; Mitchell L. Gordon; Niloofar Mireshghallah; Christopher Michael Rytting; Andre Ye; Liwei Jiang; Ximing Lu; Nouha Dziri; Tim Althoff; Yejin Choi 001 (ICML, 2024)

A Roadmap to Pluralistic Alignment. - Taylor Sorensen; Jared Moore; Jillian Fisher; Mitchell L. Gordon; Niloofar Mireshghallah; Christopher Michael Rytting; Andre Ye; Liwei Jiang; Ximing Lu; Nouha Dziri; Tim Althoff; Yejin Choi 001 (CoRR, 2024)