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Recursive Multi-Agent Systems research paper by Stanford University, 2026

Stanford University · Apr 28, 2026 · Agents and evaluation · 6 citations · 235 upvotes · unverified

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What it shows

RecursiveMAS extends recursive scaling principles from single models to multi-agent systems, enabling collaborative reasoning through iterative latent-space computations with improved efficiency and accuracy.

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

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About this paper
Authors
Xiyuan Yang, Jiaru Zou, Rui Pan and 9 more
arXiv
2604.25917 · PDF
Venue
arXiv.org
Citations
6, 0 influential · Semantic Scholar
Upvotes
235 · Hugging Face
Code
github.com/RecursiveMAS/RecursiveMAS
Lab
Stanford University

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 6Sep 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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