Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing
The episode discusses the paper 'Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing,' which introduces P-Bench, a benchmark of 425 expert-verified hypothesis-testing tasks, and Fisher-R1, an open-weight agent trained to outperform frontier models like GPT-5.4 on strict statistical accuracy. The hosts highlight the failure mode where agents produce precise p-values from invalid tests, and the training pipeline using synthetic data and outcome-grounded rewards.