CollabFlow separates collaboration design from task execution.
Agents improve collaboration by learning teams and evidence-gated communication
CollabFlow repeatedly trains a team-building director from execution outcomes while preserving multiple high-performing collaboration strategies.
Top University
Xiao Huang · Mingda Zhang · Junming Zhang · Qiang Huang · Hanwen Zhang · Yue Dai · +2 more
The Chinese University of Hong Kong, Shenzhen · Fudan University · University of Oxford
Research Digest··3 min read
Thread:Multi-Agent Coordination
Huang and colleagues present CollabFlow, a multi-agent system that learns how to assemble agents, connect them and regulate their communication using results from previous tasks.
Why this paper
From The Chinese University of Hong Kong, Shenzhen and 2 others · Part of Multi-Agent Coordination, now 33 papers
In one line
CollabFlow improves multi-agent collaboration through recursive self-improvement with evidence-conditioned communication and flow-based team credit.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ·No stated limitations found
- ·No benchmark numbers found
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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