FlowEvo: Self-Evolving Agents through the Co-Evolution of Workflows and Executable Skills
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arXiv:2607.21596v1 Announce Type: new Abstract: Large language model agents increasingly solve complex tasks by constructing inference-time workflows that combine reasoning, tool use, and code execution. While such workflows enable flexible problem solving, the useful procedures discovered during execution are often transient: they help solve the current task but are not retained in a form that can systematically benefit future tasks. We present FlowEvo, a training-free framework that compiles…
1Key Takeaways
- arXiv:2607.21596v1 Announce Type: new Abstract: Large language model agents increasingly solve complex tasks by constructing inference-time workflows that combine reasoning, tool use, and code execution.
- While such workflows enable flexible problem solving, the useful procedures discovered during execution are often transient: they help solve the current task but are not retained in a form that can systematically benefit future tasks.
- We present FlowEvo, a training-free framework that compiles….
2AIWedia Score
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3Why it matters
Research breakthroughs often arrive in products months later—early signals matter for strategy. arXiv cs.AI reports that arXiv:2607.21596v1 Announce Type: new Abstract: Large language model agents increasingly solve complex tasks by constructing inference-time workflows that combine reasoning, tool use, and code execution.
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