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Simple Lean 4 harness h1 matches specialized prover workflows

Original title: h1: A Taste of the Bitter Lesson in Automated Theorem Proving

Hugging Face daily papersby Skander Moalla, Ahmad Rammal, Niket Patel ()1 min read1
Part of a story covered by 2 sourcesEasyProver proves 1,054 of 2,000 Aegis Lean statementsMerged summary & timeline
AI summary · x-ai/grok-4.7Summaries by Vani AI

With matched models, a single attempt plus verifier feedback solved eight open FormalConjectures problems and led three formal benchmarks.

The paper introduces h1, a harness that gives a model an interface to Lean 4 and continues via verifier feedback and self-reflection without a fixed decomposition or search structure. The authors say h1 reaches state-of-the-art results on PutnamBench, FATE-X, and FormalConjectures100-Solved and settles eight open problems in FormalConjectures. At matched models it matches or beats Goedel-Architect and AlphaProof Nexus, and pass@1 often solves open problems. Ablations against Claude Code and AxProverBase attribute cost and solve rate largely to the Lean interface.

Unconfirmed: Benchmark leadership and the eight solved problems are the authors' claims from their comparisons.

Key facts
  • h1 does not impose planning, decomposition, or a search structure.
  • It reports state-of-the-art results on PutnamBench, FATE-X, and FormalConjectures100-Solved.
  • Eight open FormalConjectures problems were settled.
  • Authors say an efficient Lean interface largely determines cost and solve rate.
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From the original article

1 min read at huggingface.co

While progress in informal mathematics has come largely from scaling the chain-of-thought and agentic reasoning of frontier language models, formal theorem proving has increasingly relied on human-designed workflows around these models, such as planning, decomposition, and orchestrating specialized provers.

Hugging Face daily papers

By Skander Moalla, Ahmad Rammal, Niket Patel · huggingface.co

Read the full article at Hugging Face daily papers

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.