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NeurIPS 2026The Hebrew University of JerusalTechnion and MITMITLearning theory

A Theory of Online Learning with Autoregressive Chain-of-Thought Reasoning

Online autoregressive learning mistake bounds grow from constant to logarithmic in generation horizon M with end-to-end feedback, but chain-of-thought access removes M dependence entirely.

Idan Mehalel, Ilan Doron-Arad, Elchanan Mossel

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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medium 4/10
strict 3/5
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NeurIPS 2026The Hebrew University of JerusalNew YorkHebrew University of JerusalemColumbia University, GoogleLLM reasoning & chain of thought

Discrete Diffusion Models Exploit Asymmetry to Solve Lookahead Planning Tasks

Discrete diffusion models exploit reverse generation asymmetry to solve lookahead planning with exponentially less data and shallower architectures than autoregressive models.

Itamar Trainin, Shauli Ravfogel, Omri Abend, Amir Feder

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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AI panel: 10 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 1/5