This AI just wrote a full academic paper — from idea to citations

What if you could type a single idea — like "How does data augmentation affect small-sample image classification?" — and get back a complete academic paper with real citations, working experiments, and even an AI peer review? That's exactly what AutoResearchClaw does.

This free, open-source tool just crossed 7,100 GitHub stars and is trending globally. It runs a fully autonomous 23-stage pipeline (a series of automated steps) that transforms a single sentence into a conference-ready paper — formatted for top venues like NeurIPS, ICML, and ICLR (the world's most prestigious AI conferences).

From one sentence to a 6,000-word paper — here's how it works

The pipeline runs through 8 phases and 23 stages, each fully automated:

It actually catches fake citations

One of the biggest problems with AI-generated text is hallucinated references — citations that look real but don't exist. AutoResearchClaw attacks this with a 4-layer verification system:

1. Checks arXiv IDs against the actual database
2. Validates DOIs (digital object identifiers — unique codes for published papers) through CrossRef and DataCite
3. Cross-references against Semantic Scholar records
4. Uses AI scoring to check if the cited paper actually supports the claim

The result: every citation in the final paper points to a real, verifiable source.

It learns from its own failures

The optional MetaClaw system (a self-learning module) captures what went wrong in each run and converts failures into reusable lessons. In controlled tests, this delivered:

• 24.8% fewer retries across pipeline stages
• 40% fewer refinement cycles needed
• 18.3% overall robustness improvement

In other words, the more you use it, the better it gets.

Who is this actually for?

Graduate students and academics: Use it as a starting point for literature reviews and experiment design. It won't replace your expertise, but it can save days of preliminary work.

Startup founders and product teams: Need a quick feasibility study on a technical approach? AutoResearchClaw can generate a structured analysis with real data in hours instead of weeks.

AI enthusiasts learning to do research: It's a masterclass in how research papers are structured — watch the pipeline work and learn the process.

Try it yourself

git clone https://github.com/aiming-lab/AutoResearchClaw.git
cd AutoResearchClaw
python3 -m venv .venv && source .venv/bin/activate
pip install -e .
researchclaw setup && researchclaw init
researchclaw run --topic "Your research idea here" --auto-approve

You'll need Python 3.11+, an API key for an LLM provider (OpenAI, DeepSeek, or others), and optionally Docker and LaTeX for PDF generation. It also works with Claude Code and other AI coding assistants through the ACP protocol.

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