arXiv (All)
open access
Same Beliefs, Different Policies: Learning Reusable Representations for Early Stopping in LLM Reasoning
Reasoning LLMs often continue reasoning after reaching a correct answer, wasting computation and sometimes replacing it with an incorrect one. Deciding when to stop is a metareasoning problem: the model must weigh what further reasoning could achieve against its cost, given what it can already answe
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
- </think> Doesn't Stop Reasoning: Analysis of Spurious CoT Termination#926532
- Settle: Learning When to Stop Reasoning#1143964
- HEAL: Hindsight Entropy-Assisted Learning for Reasoning Distillation#819312
- HEAL: Hindsight Entropy-Assisted Learning for Reasoning Distillation#809319
- When Can LLMs Learn to Reason with Weak Supervision?#120495
Record · ID 1423242
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