arXiv (All)
open access
Objects Without Morphisms: What LLMs for Mathematics Do Not Represent
Large language models (LLMs) have reached expert-level performance on competition mathematics largely through the volume of search placed around them: candidate solutions are sampled in quantity and retained only when an external criterion accepts them. Such a procedure improves the outcome that sur
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
- Objects Without Morphisms: What LLMs for Mathematics Do Not Represent#1181641
- What is the Role of Small Models in the LLM Era: A Survey#1049587
- Simulating Student-Tutor Interactions with LLMs for Multilingual Math Feedback#1325015
- Do LLMs Overthink Basic Math Reasoning? Benchmarking the Accuracy-Efficiency Tradeoff in Language Models#160912
- The Cost of Inline Definitions: Vocabulary Support in English-Language Math Problem Solving#1089872
Record · ID 1188229
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