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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. STAR-PólyaMath: Multi-Agent Reasoning under Persistent Meta-Strategic Supervision

    A new multi-agent framework called STAR-PólyaMath has been introduced to improve mathematical reasoning in AI models. This system addresses issues like hallucination accumulation and memory fragmentation by employing meta-level supervision and structured interaction between reasoners and verifiers. STAR-PólyaMath achieved state-of-the-art results on eight competition benchmarks, including perfect scores on AIME, Putnam, and HMMT, significantly outperforming existing baselines. AI

    STAR-PólyaMath: Multi-Agent Reasoning under Persistent Meta-Strategic Supervision

    IMPACT Sets new SOTA on math reasoning benchmarks, potentially improving AI's capability in complex problem-solving.