2026-09-23T16:01:56.171Z
- url:
https://arxiv.org/abs/2609.19759v1→ https://arxiv.org/abs/2609.19759
SOURCE-LINKED INTELLIGENCE
Rethinking Multi-Agent Collaboration: When More Is Less
The rapid advancement of large language models and single-agent harnesses has reshaped the landscape of autonomous systems, raising a critical question of when multi-agent collaboration offers genuine value. As individual agent capabilities continue to scale, multi-agent collaboration faces diminishing returns while incurring growing context overhead. Through systematic analysis, we delineate the capability boundaries of multi-agent collaboration relative to single-agent alternatives, showing that it confers systematic benefits specifically in long-horizon tasks with sparse dependencies, while
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T06:29:12.000Z
- arXiv · Artificial Intelligence · 2026-09-17T06:29:12.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.
Observed changes
AIIC observation times, not verified publisher revision times. Up to eight recent revisions.