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Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning research paper by NVIDIA, 2026

NVIDIA · Jan 14, 2026 · Reasoning · 22 citations · 54 upvotes · unverified

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What it shows

Fast-ThinkAct is an efficient vision-language-action framework that reduces inference latency by 89.3% through compact latent reasoning while maintaining long-horizon planning and few-shot adaptation capabilities.

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

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About this paper
Authors
Chi-Pin Huang, Yunze Man, Zhiding Yu and 4 more
arXiv
2601.09708 · PDF
Venue
arXiv.org
Citations
22, 2 influential · Semantic Scholar
Upvotes
54 · Hugging Face
Lab
NVIDIA · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 2Sep 25, 2026
Citationsfirst count: 22Sep 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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