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Beyond Selected Breakthroughs: Evaluating Language Models on Randomly Sampled Mathematical Conjectures· 超越特定突破:在随机数学猜想上评估语言模型

The last year has seen a shift in AI-assisted mathematics, with frontier language models producing proofs of and counterexamples to long-standing open conjectures. However, studying only the current set of major breakthroughs provides an incomplete picture of LLM capabilities and the computational resources needed to achieve reported results. To address this, we introduce a new dataset, OpenConjecture, which collects conjectures from mathematics papers published on the arXiv since February 2026. We use these conjectures as a source of open mathematical problems, and apply frontier GPT models to a random sample of 200 of these conjectures over three passes using a reproducible protocol without problem-specific mathematical guidance. Rather than attempt expert verification of these candidate

领域:cs.AI作者:Helen Jenne、Davis Brown、Jesse He
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