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Attention Illuminates LLM Reasoning: The Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization research paper by Alibaba (Qwen), 2025

Alibaba (Qwen) · Oct 15, 2025 · Reasoning · 27 citations · 59 upvotes · unverified

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What it shows

Attention mechanisms in LLMs are analyzed to reveal reasoning patterns, leading to novel RL strategies that improve performance by focusing on critical tokens.

UnverifiedHugging Face's summary; not yet checked by hand.

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MolmoAct: Action Reasoning Models that can Reason in SpaceAction Reasoning Models (ARMs) integrate perception, planning, and control to enable adaptable and explainable robotic behavior, achieving superior performance across various tasks and settings.Ai2 · Aug 2025 · Unverified185
ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent PlanningThinkAct, a dual-system framework, uses reinforced visual latent planning to enable few-shot adaptation, long-horizon planning, and self-correction in embodied AI tasks by bridging high-level reasoning with low-level action execution.NVIDIA · Jul 2025 · Unverified172
About this paper
Authors
Yang Li, Zhichen Dong, Yuhan Sun and 9 more
arXiv
2510.13554 · PDF
Venue
arXiv.org
Citations
27, 2 influential · Semantic Scholar
Upvotes
59 · Hugging Face
Lab
Alibaba (Qwen) · on Companies · on Quarterly

Changes

What changed
Upvotes53 to 59 (+6)Sep 25, 2026
Influential citationsfirst count: 2Sep 25, 2026
Citationsfirst count: 27Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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