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English(EN) HypoAgent: An Agentic Framework for Interactive Abductive Hypothesis Generation over Knowledge Graphs

HypoAgent框架增强交互式假设生成

研究人员开发了HypoAgent,一个用于知识图谱上交互式溯因假设生成的新框架。该系统通过更好地处理对话中不断变化的自然语言意图并为失败的假设提供详细的诊断,解决了当前方法的局限性。HypoAgent集成了三个专业代理来识别用户意图、生成假设以及分析根本原因以进行改进,在各种场景中均展示了最先进的性能。 AI

影响 增强了AI在复杂知识图谱环境中交互式生成和改进假设的能力。

排序理由 该集群包含一篇详细介绍新AI研究框架的学术论文。

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Yisen Gao, Yixi Cai, Tianshi Zheng, Jiaxin Bai, Yangqiu Song ·

    HypoAgent: An Agentic Framework for Interactive Abductive Hypothesis Generation over Knowledge Graphs

    arXiv:2605.31370v1 Announce Type: new Abstract: Abductive reasoning over knowledge graphs aims to generate logical hypotheses that explain observed entities or facts. Existing controllable hypothesis generation methods allow users to guide this process with explicit conditions, b…

  2. arXiv cs.AI TIER_1 English(EN) · Yangqiu Song ·

    HypoAgent:用于知识图谱交互式溯因假设生成的代理框架

    Abductive reasoning over knowledge graphs aims to generate logical hypotheses that explain observed entities or facts. Existing controllable hypothesis generation methods allow users to guide this process with explicit conditions, but they remain limited in interactive settings: …