English(EN) DHCG: Dynamic Construction of Hierarchical Collaboration Graphs for LLM-Based Multi-Agent Reasoning

新的DHCG框架通过动态协作图增强LLM多智能体推理能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 04:00

研究人员推出了一种新颖的DHCG框架，用于在LLM驱动的多智能体系统中构建动态分层协作图。该方法通过实现动态组合、减少错位依赖并提供灵活的可扩展性，解决了现有方法的局限性。DHCG协调规划器（Planner）、工作者（Worker）和生成器（Generator）模块，根据查询和执行反馈构建协作图，在代码生成、数学推理和领域特定任务中取得了最先进的性能。 AI

影响通过实现动态协作图构建，增强了LLM多智能体系统，有望提高复杂推理任务的性能。

排序理由该集群包含一篇学术论文，详细介绍了LLM驱动的多智能体推理的新框架和方法论。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Jie Ren, Jiakang Yuan, Chenyu Huang, Hezeer Ma, Jiayuan Fan, Tao Chen · 2026-10-07 04:00

DHCG：基于LLM的多智能体推理的动态分层协作图构建

arXiv:2610.07835v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have demonstrated strong capabilities in solving complex problems across diverse domains. Recently, the dynamic orchestration of agent systems has become an important research direction. However, …

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报道来源 [1]

DHCG：基于LLM的多智能体推理的动态分层协作图构建

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