Fairness, Bias, and Factuality in LLMs

This workshop brings together researchers and practitioners in the field of LLMs and security to discuss the topic of fairness and factuality in large language models. There is a series of talks given from various perspectives in the field, after which attendees discuss and collaborate in breakout sessions.

Speakers

• Aylin Caliskan, Assistant Professor,, The Information School, University of Washington
• Cindy Bennet, Senior Research Scientist, Google
• Irene Chen, Assistant Professor, Computational Precision Health Program, University of California, Berkeley; Assistant Professor, Computational Precision Health Program, University of California, San Francisco
• Peter Henderson, Assistant Professor, Department of Computer Science and School of Public and International Affairs, Princeton University
• William Agnew, Carnegie Bosch Postdoctoral Fellow, Carnegie Mellon University
• Christina Pöpper, Program Head of Computer Science and Associate Professor of Computer Science; NYUAD; Global Network Associate Professor of Computer Science, Courant Institute of Mathematical Sciences , NYU