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Google's Stellar Colosseum tackles long-horizon math proofs with Gemini models

Google Research has developed a novel multi-agent system called Stellar Colosseum, designed to tackle long-horizon tasks, particularly in mathematical proofs. This system operates in stages, generating candidate solutions in parallel, subjecting them to targeted falsification, and merging them with critiques. When utilized with Gemini 3.1 Pro and Gemini 3.7 Flash, Stellar Colosseum achieved a 71.0% success rate on the TCS-Bench benchmark for theorem-proving tasks and solved 218 out of 222 Codeforces problems. AI

IMPACT This multi-agent approach could advance AI capabilities in complex problem-solving and theorem proving.

RANK_REASON The cluster describes a research paper detailing a new AI system and its performance on benchmarks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on X — Omar Sanseviero (HF research) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Google's Stellar Colosseum tackles long-horizon math proofs with Gemini models

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The cluster describes a research paper detailing a new AI system and its performance on benchmarks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. X — Omar Sanseviero (HF research) TIER_1 Norsk(NO) · omarsar0 ·

    Banger paper from Google on agent harnesses for long-horizon tasks.

    Banger paper from Google on agent harnesses for long-horizon tasks. (bookmark it) Google Research built a many-agent harness for long mathematical proofs, and it produced new results on open problems from FOCS and JMLR papers. Stellar Colosseum works in stages. It explores ht…