arXiv (All)
open access
Think Right: Learning to Mitigate Under-Over Thinking via Adaptive, Attentive Compression
Recent thinking models are capable of solving complex reasoning tasks by scaling test-time compute, but this scaling should be allocated in line with task difficulty. On one hand, short reasoning (underthinking) leads to errors on harder problems that require extended reasoning steps; but, excessive
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
- To Think or Not to Think: Allocating Reasoning Where It Helps#1077591
- </think> Doesn't Stop Reasoning: Analysis of Spurious CoT Termination#926532
- LatentHarness: Learning Latent Actions for Memory and Reasoning via Counterfactual Policy Distillation#1144907
- When Compression Helps and When It Hurts: Condition-Aware Analysis of Chain-of-Thought Distillation#820519
- Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models#984842
Record · ID 1144735
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