# Researchers Target the Token Bill of Reasoning Models With Entropy-Based Early Resolution

The proposed method stops a chain of thought when the model's next-token uncertainty resolves, rather than letting reinforcement-trained models generate long traces by default.

- Published: 2026-09-01T06:29:06.347Z
- Canonical: https://polylog.news/ai/2026-09-01/researchers-target-the-token-bill-of-reasoning-models-with-e
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [arXiv cs.LG](https://arxiv.org/abs/2608.28771), [Anthropic News](https://www.anthropic.com/news/claude-opus-5)

A paper posted to arXiv, ERR+: Sequential Entropy Resolution for Efficient and Decisive LLM Reasoning, addresses a known cost problem in large reasoning models. Models trained with reinforcement learning from verifiable rewards learn to pro…

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