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MM-Zero: Self-Evolving Multi-Model Vision Language Models From Zero Data research paper by NVIDIA, 2026

NVIDIA · Mar 10, 2026 · Multimodal and robotics · 16 citations · 55 upvotes · unverified

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What it shows

MM-Zero enables zero-data self-evolution of vision-language models through a multi-role framework with proposer, coder, and solver components trained via group relative policy optimization.

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

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About this paper
Authors
Zongxia Li, Hongyang Du, Chengsong Huang and 8 more
arXiv
2603.09206 · PDF
Venue
arXiv.org
Citations
16, 1 influential · Semantic Scholar
Upvotes
55 · Hugging Face
Code
github.com/zli12321/MM-Zero
Lab
NVIDIA · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 1Sep 25, 2026
Citationsfirst count: 16Sep 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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