Summary of Chatgraph: Chat with Your Graphs, by Yun Peng et al.
ChatGraph: Chat with Your Graphs
by Yun Peng, Sen Lin, Qian Chen, Lyu Xu, Xiaojun Ren, Yafei Li, Jianliang Xu
First submitted to arxiv on: 23 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed framework, ChatGraph, revolutionizes graph analysis by allowing users to interact with graph data through natural language. This large language model (LLM)-based framework is designed to overcome the limitations of traditional approaches, which either require high programming skills or limited functionalities. By generating chains of graph analysis APIs based on user prompts, ChatGraph enables users to easily and flexibly analyze graphs without requiring extensive technical expertise. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ChatGraph makes it easy for anyone to work with graph data! It’s like having a super smart assistant that understands what you want to do with your graphs. You can tell it what you want to analyze, and it will find the right tools to help you get the job done. This is a big deal because currently, people need to know how to code or use special software just to work with graph data. |
Keywords
» Artificial intelligence » Large language model
