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Chain-of-Visual-Thought: Teaching VLMs to See and Think Better with Continuous Visual Tokens research paper by UC Berkeley, 2025

UC Berkeley · Nov 24, 2025 · Reasoning · 62 citations · 29 upvotes · unverified

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What it shows

Chain-of-Visual-Thought (COVT) enables Vision-Language Models to reason through visual tokens, improving their performance on perceptual tasks by capturing dense visual information.

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

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About this paper
Authors
Yiming Qin, Bomin Wei, Jiaxin Ge and 4 more
arXiv
2511.19418 · PDF
Venue
arXiv.org
Citations
62, 7 influential · Semantic Scholar
Upvotes
29 · Hugging Face
Code
github.com/Wakals/CoVT
Lab
UC Berkeley

Changes

What changed
Influential citationsfirst count: 7Sep 25, 2026
Citationsfirst count: 62Sep 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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