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State of Thought Enables Endogenous Reasoning

arXiv · AI, language, vision and robotics · article · Sep 13, 2026 · UTC

Test-time compute has emerged as a major approach to improving the capabilities of Large Language Models (LLMs). However, existing test-time reasoning paradigms rely heavily on externally imposed control, either through fixed reasoning programs or through costly expansion in constrained search spaces, limiting both generalization and efficiency. We propose State of Thought (SoT), a new reasoning paradigm that enables endogenous reasoning in LLMs, with the model's internal reasoning state governing how reasoning unfolds. Concretely, SoT extracts a compact dynamics-geometric state from the model

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First collected: 2026-09-20T12:41:04.663Z. This is not the publication date.