Assistant Professor, George Washington University
2 papers at NeurIPS 2025
We build a LM-based system that can outperfrom expert AI researchers in predicting the outcomes of empirical AI research ideas, without running actual experiments.
Debate between AI experts outperforms single-advisor consultancy in helping humans make more accurate factual judgments, especially benefiting those with mainstream beliefs.