Argument Graph Uncertainty: Quantifying Uncertainty from the Logical Structure of Reasoning Chains

14 Oct 2026Reported by arXiv21

Argument Graph Uncertainty: Quantifying Uncertainty from the Logical Structure of Reasoning Chains. The story centres on Reasoning Models. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.

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Reasoning Modelstopic

Reported by arXiv

First seen 14 oct 2026

arXivArgument Graph Uncertainty: Quantifying Uncertainty from the Logical Structure of Reasoning Chains14 Oct 2026Simon Baur

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arXiv28 Sept 2026

AI Models24

Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models

Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models. It centres on Reasoning Models, and also names GPT and Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models and AI Tools — the section covering a new or updated model, its capabilities, benchmarks or availability.

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Argument Graph Uncertainty: Quantifying Uncertainty from the Logical Structure of Reasoning Chains

Companies, models and people in this story

Reported by arXiv

Reasoning with Continuous Latent Diffusion

Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models

Transcribe, Translate, and Optimize: Joint Reward Learning for Speech Translation

Spoken Language Models that Think Aloud

Companies, models and people in this story

Reported by arXiv

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Reasoning with Continuous Latent Diffusion

Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models

Transcribe, Translate, and Optimize: Joint Reward Learning for Speech Translation

Spoken Language Models that Think Aloud