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Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players research paper by NVIDIA, 2026

NVIDIA · May 27, 2026 · Agents and evaluation · 7 citations · 148 upvotes · unverified

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What it shows

A generative multi-agent world model is presented that uses simplex rotary agent encoding and sparse hub attention to enable scalable, permutation-symmetric interaction between multiple agents in interactive video generation.

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

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About this paper
Authors
Fangfu Liu, Kai He, Tianchang Shen and 7 more
arXiv
2605.28816 · PDF
Venue
arXiv.org
Citations
7, 0 influential · Semantic Scholar
Upvotes
148 · Hugging Face
Lab
NVIDIA · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 7Sep 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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