EvoSteer represents a multi-agent workflow as an executable communication graph, with nodes assigned roles and skills and edges defining how agents exchange information.
EvoSteer Repairs Multi-Agent Workflows While They Are Still Running
The system uses reference-based credit assignment and statistically validated skills to revise an agent graph during execution.
Top University
Mingda Zhang · Hanwen Zhang · Qiang Huang · Zijia Wang · Pengfei Guo · Yuchen Zhang · +2 more
The Chinese University of Hong Kong, Shenzhen · Dalian University of Technology · Fudan University · University of Oxford · North China Electric Power University
Research Digest··3 min read
Thread:Multi-Agent Coordination
Zhang et al.
Why this paper
From The Chinese University of Hong Kong, Shenzhen and 5 others · Released code · Part of Multi-Agent Coordination, now 34 papers
In one line
EvoSteer outperforms baselines across twelve datasets with online self-evolving graph orchestration using AnchorTB and validated skill admission.
What it released
Code
What we could check
- ✓Code link in the paper (github.com)
- ·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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