explaingit

kaixindelele/chatpaper

★ 19,492PythonAudience · researcherComplexity · 2/5MaintainedSetup · moderate

TLDR

Python tool that uses ChatGPT to automatically summarize academic papers from arXiv, helping researchers stay current without reading full papers.

Mindmap

mindmap
  root((ChatPaper))
    What it does
      Summarize papers
      Download from arXiv
      Analyze strengths
      Draft responses
    Inputs
      Keywords
      PDF files
      Paper URLs
    Outputs
      Structured summaries
      Weakness analysis
      Reviewer replies
    Use cases
      Literature surveys
      Paper screening
      Manuscript review
    Tech stack
      Python
      ChatGPT API
    Audience
      Researchers
      PhD students

Things people build with this

USE CASE 1

Survey a research subfield in one evening by reading AI-generated summaries instead of full papers.

USE CASE 2

Screen dozens of new arXiv papers weekly to identify which ones are worth reading in full.

USE CASE 3

Analyze a paper's strengths and weaknesses automatically before deciding to cite or build on it.

USE CASE 4

Draft responses to peer reviewer comments on your own manuscript.

Tech stack

PythonChatGPT API

Getting it running

Difficulty · moderate Time to first run · 30min

Requires a valid OpenAI API key and account with available credits.

License could not be detected automatically. Check the repository's LICENSE file before use.

In plain English

ChatPaper is a Python tool that uses ChatGPT to help researchers rapidly digest academic papers, especially those published on arXiv. The problem it solves is keeping up with the relentless flood of new AI and scientific papers, reading dozens of full papers each week is impractical, so ChatPaper lets you scan summaries instead. The workflow is straightforward: you provide keywords or a local PDF file, the tool automatically downloads the latest matching papers from arXiv, then sends them to ChatGPT's API to produce structured summaries in a consistent format. Beyond summarizing, the tool suite also includes ChatReviewer (which analyzes a paper's strengths and weaknesses), ChatImprovement (which polishes draft manuscripts), and ChatResponse (which drafts replies to reviewer comments). The goal is to let someone survey an entire subfield in an evening rather than over weeks. You would use this if you are a researcher, PhD student, or technical professional who needs to stay current with academic literature without reading every paper in full. The tech stack is Python using the ChatGPT API.

Copy-paste prompts

Prompt 1
I have 50 new arXiv papers on transformer architectures. How do I use ChatPaper to summarize them all at once and get a CSV of key findings?
Prompt 2
Show me how to set up ChatPaper with my ChatGPT API key and scan papers matching the keyword 'diffusion models'.
Prompt 3
I have a PDF of my draft paper. How do I use ChatImprovement to get ChatGPT's suggestions for improving clarity and structure?
Prompt 4
Walk me through using ChatReviewer to analyze the strengths and weaknesses of a paper I'm considering citing.
Prompt 5
How do I use ChatResponse to draft a reply to reviewer comments on my submitted manuscript?
Open on GitHub → Explain another repo

Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.