Semi-Autonomous Mathematics Discovery with Gemini: A Case Study on the Erdős Problems
- Published
- Source
- arXiv
- Paper number
- 113
- Field
- Math / Scientific AI
- arXiv ID
- 2601.22401
Key points
- Many problems in the Erdős Problems database are labeled as Open, but some may already have existing solutions that are simply not well known.
- Human mathematicians face an attention bottleneck when they try to systematically evaluate a large number of unproven conjectures and conduct broad literature searches.
- Rigorous benchmarking of advanced large language models on complex mathematical problem solving requires suitable and diverse datasets.
- A specialized Gemini-based AI agent called Aletheia was tasked with generating candidate solutions for 700 Open Erdős problems and performing an initial natural-language verification.
- A strict multi-stage human evaluation framework, including expert filtering, detailed review, and external consultation, was used to judge the correctness and novelty of the AI outputs.
- Extensive literature searches and analysis of AI reasoning logs were conducted to distinguish genuinely new results from independent rediscovery or confirmed existing solutions.
Paper links
External research summaries. These are not HDATF publications or measured product results.