arXiv (All)
open access
CCQA: Generating Question from Solution Can Improve Inference-Time Reasoning in SLMs
Recently, inference-time reasoning strategies have further improved the accuracy of large language models (LLMs), but their effectiveness on smaller models remains unclear. Based on the observation that conventional approaches often fail to improve performance in this context, we propose \textbf{C}y
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
- Unifying Conformal Language Tasks with In-Context Ensembles#925378
- Unifying Conformal Language Tasks with In-Context Ensembles#921142
- LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models#328737
- EvoMO-SR: Multiobjective LLM-based Evolution of Symbolic Expressions with substructure guidance#1131029
- SymbolicLM: Training Language Models as Symbolic Regressors#1118306
Record · ID 1141439
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