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When Should LLMs Reason? Adaptive Inference Routing via Entropy Dynamics
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Researchers introduced adaptive inference routing using early decoding entropy to determine when chain-of-thought reasoning is cost-effective.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 23 October 2026
- Collected by OneBench
- 24 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2605.22873v3 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) reasoning can improve LLM performance, but its benefits vary across tasks, models, and individual queries. On some tasks,…
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