Papers by Yulang Chen

1 papers
AgentSlimming: Towards Efficient and Cost-Aware Multi-Agent Systems (2026.acl-long)

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Challenge: Automated expansion methods often result in bloated structures with redundant agents, leading to excessive token consumption.
Approach: They propose a plug-and-play compression framework for graph-structured multi-agent workflows . they estimate the importance score of each agent and remove redundant agents .
Outcome: Experiments show that AgentSlimming reduces average token cost by 78.9% with negligible performance degradation.

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