The authors represented exploration as a shared graph containing facts and intents.
Fact-intent graphs accelerate multi-agent work on difficult, long-running tasks
CAIRN coordinated parallel agents through a shared dependency graph, reducing solution time mainly on tasks requiring at least one million tokens.
Chinese Tech
Zuyao Xu · Yuyang Jia · Junwei Guan · Xiang Li · Kaiwen Shen · Zhiqiang Dong
Nankai University · Tencent Security Yunding Lab · Tsinghua University
Research Digest··2 min read
Xu and colleagues introduce CAIRN, a multi-agent architecture that records findings and proposed investigations in a persistent directed acyclic graph.
Why this paper
From Tencent Security Yunding Lab and 2 others
In one line
CAIRN coordinates multiple LLM agents using a dynamic fact-intent DAG, achieving up to 3.08x speedups on high-effort tasks over 1M tokens.
What we could check
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