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StochBench: A Domain-Specific Benchmark for Stochastic Processes in Lean

arXiv · AI, language, vision and robotics · article · Sep 8, 2026 · UTC

Leading benchmarks for formal theorem proving with large language models are small collections drawn from competition math, such as the IMO and Putnam, that poorly represent field-specific applications. We introduce StochBench, a Lean 4 benchmark of 450 graduate stochastic-processes problems at varying abstraction levels, each paired with its natural-language source. Addressing a field underrepresented in Mathlib, it covers finite and countable Markov chains, renewal processes, random walks, martingales, stopping times, queues, Brownian motion, stochastic calculus, weak convergence, and Poisso

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Evidence & attribution

First collected: 2026-09-20T20:02:11.508Z. This is not the publication date.