LLM-based multi-agent systems (MAS) rely on collaboration among specialized agents to solve complex tasks. Existing methods improve MAS by refining the prompts, skills, and execution strategies of ind
EvoTeam evolves multi-agent collaboration by jointly adapting team organization, interaction rules, and agent skills through execution experience while maintaining reusable team libraries.
LLM-based multi-agent systems (MAS) rely on collaboration among specialized agents to solve complex tasks. Existing methods improve MAS by refining the prompts, skills, and execution strategies of individual agents based on task feedback. However, improving individual agents does not necessarily lead to better team collaboration. Recent studies have therefore extended evolution to the collaboration level, using collective execution experience to adjust team organization, and inter-agent interactions. Nevertheless, evolving collaboration across heterogeneous tasks remains challenging, as existing approaches often constrain team reorganization within a shared structure and reuse interaction…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
EvoTeam: Multi-Agent Collaboration via Evolving Teams was first seen on Hugging Face · Daily papers on Nov 4, 2026. Since then it has appeared in 15 checks on 2 different days. Its best position was #8 of 30, reached on Nov 5, 07:28 UTC. It dropped off the list after Nov 5, 11:28 UTC.
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Not at the moment. It was last on the list on Nov 5, 11:28 UTC, after 2 days of trending.
#8 on Hugging Face · Daily papers, on Nov 5, 07:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 4, 2026 and has been on the list on 2 days (15 checks) since.