arXiv (All)
open access
Proof2Hybrid: Automatic Mathematical Benchmark Synthesis for Proof-Centric Problems
Evaluating the mathematical capability of Large Language Models (LLMs) is a critical yet challenging frontier. Existing benchmarks fall short, particularly for proof-centric problems, as manual creation is unscalable and costly, leaving the true mathematical abilities of LLMs largely unassessed. To
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Proof2Hybrid: Automatic Mathematical Benchmark Synthesis for Proof-Centric Problems#788648
- AdvancedMathBench: A Benchmark Suite for Advanced Mathematical Proof Generation and Verification#1141603
- Official Review · ICLR 2026#787116
- What is the Role of Small Models in the LLM Era: A Survey#1049587
- Do LLMs Overthink Basic Math Reasoning? Benchmarking the Accuracy-Efficiency Tradeoff in Language Models#160912
Record · ID 792648
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive