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Microsoft Research says Xinzhi Zhang and Zhao Song prove KLS conjecture with AI

Microsoft Research announced that senior researcher Xinzhi Zhang and collaborator Zhao Song have proved the Kannan–Lovász–Simonovits (KLS) conjecture, a 31‑year‑old problem in high‑dimensional geometry and probability. Their 140‑page paper “An O(1) Bound for the KLS Constant” was first submitted to arXiv on Oct 1, 2026 and revised on Oct 4, 2026, with Zhang as submitting author. The abstract…

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Key points

  • Xinzhi Zhang and Zhao Song proved the 31‑year‑old KLS conjecture, publishing a 140‑page paper on arXiv.
  • The proof used a human‑directed agentic AI process that explored over 100 candidate approaches.
  • Independent parallel proofs were posted the same day, including a 32‑page paper and a Lean formalization with a 500 bound.

The researchers used a human‑directed, agentic AI research process. Over 100 candidate approaches were explored by multiple AI agents, with the team pruning and iterating the most promising ideas. The recursive refinement ultimately removed any dimension‑dependent term, yielding a fixed bound. AI tools also assisted with derivations, manuscript preparation, and internal proof checks. Roughly one hundred research trajectories were examined before the breakthrough.

Independent groups posted parallel proofs the same day, including a 32‑page paper by Pierre Bizeul, Boaz Klartag and Joseph Lehec, and a Lean 4 formalization “KLS500” that verified a dimension‑free Poincaré constant bound of 500, rebuilding 1,710 modules. The Microsoft team plans to release a shortened proof and its Lean verification after review.

Full story from Unite.AI · by Jonas Reeve, Cognitive AI & AGI, AI Research AgentOpen source ↗

Microsoft Researcher and Collaborator Prove 31-Year-Old KLS Conjecture

Unite.AI · 21 October 2026

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This text was published by Unite.AI and written by Jonas Reeve, Cognitive AI & AGI, AI Research Agent. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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Microsoft ResearchXinzhi ZhangZhao SongVictor ReisIshai MenachePierre BizeulBoaz Klartag

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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