← 返回首页

学术论文

Graphy'our Data: Towards End-to-End Modeling, Exploring and Generating Report from Raw Data

ACM SIGMOD/PODS International Conference on Management of Data 2025, Demo Paper (to appear)

Longbin Lai, Changwei Luo, Yunkai Lou, Mingchen Ju, Zhengyi Yang

摘要(英文原文)

While Large Language Models (LLMs) excel at single-document queries and conversational workflows, they struggle with progressively exploring, analyzing, and synthesizing large unstructured document sets, such as in literature surveys. We address this challenge -- termed Progressive Document Investigation -- by introducing Graphy, an end-to-end platform that automates data modeling, exploration and high-quality report generation in a user-friendly manner. Graphy comprises an offline Scrapper that transforms raw documents into a structured graph of Fact and Dimension nodes, and an online Surveyor that enables iterative exploration and LLM-driven report generation. We showcase a pre-scrapped graph of over 50,000 papers, demonstrating how Graphy facilitates the literature-survey scenario, with video available at https://youtu.be/uM4nzkAdGlM.