Congratulations to seven research projects that were selected for the Spring 2026 cohort.
- Emmanuel Candès, Stanford University: Statistically Efficient LLM Evaluation and Ranking with Pairwise Human Preference Data
- Haifeng Xu
@haifengxu0, University of Chicago: Towards a Principled Evaluation of LLMs’ Predictive Intelligence
- Lihua Lei
@lihua_lei_stat, Stanford University: Is Bradley–Terry Enough? Heterogeneous Preference Modeling for RLHF
- Negin Golrezaei
@NeginGolrezaei, Massachusetts Institute of Technology: Causal inference framework for multi-turn AI evaluation.
- Ramesh Raskar
@raskarmit, Massachusetts Institute of Technology: Toward Adaptive, Task-Conditional Evaluation for AI Agents
- Steven Wu
@zstevenwu and Andrew Ilyas
@andrew_ilyas, Carnegie Mellon University: Goodhart’s Law on the Leaderboard: Can Cheap Preference Optimization Game Arena?
-Tal Linzen
@tallinzen, New York University: A Rigorous Evaluation of Meta-Cognitive Monitoring in LLMs
Read more about the program details and submit your proposal for Fall 2026 here: