2026
OpenEstimate: Evaluating LLMs on Probabilistic Estimation with Real-World Data
ICLR 2026poster
Real-world settings where language models (LMs) are deployed---in domains spanning healthcare, finance, and other forms of knowledge work—require models to grapple with incomplete information and reason under uncertainty. Yet most LM evaluations focus on problems with well-defined answers and succes…