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Rohan Paul· @rohanpaul_ai · X· · Original publication time AI score54

Meta and NYU paper presents h1 loop for automated theorem provingMachine translation

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h1 keeps a model working after failed Lean checks, using fast feedback and search tools without a preset plan. On PutnamBench with the same model, it solved 598 problems versus 597 for the hand-built Goedel-Architect, at $1.08 versus $1.47 per problem.

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– https://t.co/8eRgx6Fg29

Title: "h1: A Taste of the Bitter Lesson in Automated Theorem Proving"

ReplyRohan Paul@rohanpaul_ai
New Meta, NYU paper shows that a simple loop with good Lean tools and more compute matches or beats hand-built theorem-proving workflows. Systems that write math proofs in Lean, a language a computer can check, increasingly use hand-designed workflows that plan and split up problems. Their gains often come with stronger models or more compute, hiding what the workflow adds. They built h1, a loop that gives the model fast Lean feedback and search tools, and keeps it working after each failed check. It imposes no plan, only a progress summary before each new round. With the same model, h1 beat the hand-built Goedel-Architect on PutnamBench, 598 problems to 597, at $1.08 against $1.47 per problem. The interface still matters: with Opus 4.8, h1 solved 83 of 100 hard algebra problems, against 63 for Claude Code.
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