English(EN) EvoSteer: Online Self-Evolving Graph Orchestration via Reference-Anchored Credit Assignment

EvoSteer框架通过在线自演化增强LLM多智能体系统

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 04:00

研究人员推出了一种新颖的框架EvoSteer，用于LLM驱动的多智能体系统的在线自演化图编排。该方法通过使编排器能够在执行过程中持续构建和修复团队，解决了事后演化和信用扩散等挑战。EvoSteer利用锚定轨迹平衡（AnchorTB）进行信用分配，并利用验证技能录取来推广新技能，在问答、数学推理和代码生成等各种任务中均表现出显著的性能提升。 AI

影响这项研究可能为复杂任务带来更高效、更具适应性的LLM驱动的多智能体系统。

排序理由这是一篇详细介绍LLM驱动的多智能体系统新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Mingda Zhang, Hanwen Zhang, Qiang Huang, Zijia Wang, Pengfei Guo, Yuchen Zhang, Jionghao Zhu, Xiaoying Tang · 2026-10-01 04:00

EvoSteer：通过参考锚定信用分配实现在线自演化图编排

arXiv:2609.38661v1 Announce Type: new Abstract: In recent years, LLM-based multi-agent systems have been widely applied to orchestrate tool-using agents into executable communication graphs. However, existing self-evolving orchestration still faces key challenges, including post-…

本文如何被排名

报道来源 [1]

EvoSteer：通过参考锚定信用分配实现在线自演化图编排

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