arXiv (All)
open access
Route-and-Generate: KL-Regularized Router Improvement for Reasoning Routing in LLMs
Large language models often apply complex reasoning indiscriminately, leading to overthinking on simple tasks and underthinking on harder ones. We present Route-and-Generate (Rouge), a hierarchical training framework that enables LLMs to adaptively decide when and how much reasoning is required for
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
- Planning with Transformers: Chain of Computation and Structured Context Windows#1296456
- Explore-on-Graph: Hybrid Embedding-LLM Reasoning for Knowledge Graph Question Answering under Incompleteness#1144953
- Explore-over-Graph: Hybrid Embedding-LLM Reasoning for Knowledge Graph Question Answering under Incompleteness#1361479
- LLM Post-Training: A Deep Dive Into Reasoning Large Language Models#1274281
- Tasks over Application Manuals: Revealing Gaps in Long-Horizon Procedural Reasoning for Language Models#1070513
Record · ID 1423143
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