Seventy3

Seventy3: 用NotebookLM将论文生成播客，让大家跟着AI一起进步。

今天的主题是：

GraphAgent: Agentic Graph Language Assistant

Summary

This paper introduces GraphAgent, a novel automated agent pipeline designed for analyzing both structured (graph) and unstructured (textual) data. GraphAgent uses three key agents: a Graph Generator Agent to create knowledge graphs from text, a Task Planning Agent to interpret user queries, and a Task Execution Agent to perform predictive or generative tasks. The system is evaluated on various datasets, showcasing superior performance compared to state-of-the-art methods in both predictive and generative tasks, particularly with smaller model sizes and zero-shot learning. The authors make their work open-source.

本文提出了GraphAgent，一种用于分析结构化（图形）和非结构化（文本）数据的新型自动化代理管道。GraphAgent 使用三个关键代理：图生成代理（Graph Generator Agent）用于从文本中创建知识图谱，任务规划代理（Task Planning Agent）用于解释用户查询，任务执行代理（Task Execution Agent）用于执行预测或生成任务。该系统在多个数据集上进行了评估，展示了在预测和生成任务中优于最先进方法的表现，特别是在较小模型和零-shot 学习的情况下。作者将其工作开源。

原文链接：https://arxiv.org/abs/2412.17029