BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces

In three linesBehaviorBench is a benchmark for evaluating personalized decision modeling from real-world behavioral traces. Built on 2,000 wallets with 141,445 belief-prediction instances and 1,485,972 trade-prediction instances, it tests whether generative models can adapt predictions to individual users without relying on simulated behavior.

Summary generated by Claude — human-verified