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Multi-User Large Language Model Agents research paper by Stanford University, 2026

Stanford University · Mar 19, 2026 · Foundation models · 2 citations · 28 upvotes · unverified

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What it shows

Multi-user large language model agents face challenges in handling conflicting objectives, privacy preservation, and coordination efficiency in multi-principal decision-making scenarios.

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

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About this paper
Authors
Shu Yang, Shenzhe Zhu, Hao Zhu and 5 more
arXiv
2604.08567 · PDF
Venue
arXiv.org
Citations
2, 0 influential · Semantic Scholar
Upvotes
28 · Hugging Face
Code
github.com/Korde-AI/Multi-User-LLM-Agent
Lab
Stanford University

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 2Sep 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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