RunPaper reads any ML research paper and gives you a complete Python scaffold — architecture, training loop, config — plus an interactive diagram and a reproducibility audit. No more reverse-engineering math into code.
One free paper upload · No credit card · 60 second setup
Five AI pipelines run in parallel in the background
Upload any ML paper PDF
arXiv papers, conference submissions, preprints — anything with text.
AI extracts & generates
5-step pipeline: structure extraction → code scaffold → reproducibility audit → architecture flowchart → Q&A pairs. Takes 60–120 seconds.
Explore, learn, and run
Interactive diagram, navigable code, PDF side-by-side, and a chat assistant — all grounded in your specific paper.
Six tabs. One uploaded PDF.
Interactive ReactFlow graph of the model's data flow. Click any node to see its math, description, and exact code snippet.
model.py, train.py, config.yaml, requirements.txt — all generated from the paper. # TODO markers flag what the paper leaves ambiguous.
Original PDF rendered alongside your code and diagram. No more tab-switching between your browser and your editor.
Title, authors, key equations (LaTeX rendered), hyperparameter table with descriptions, and clickable dataset links.
20-point checklist: ✅ specified in paper vs ❌ missing — with suggested defaults for everything underdefined.
Ask questions grounded in the paper and code. Switch to Socratic mode and the AI guides your thinking instead of just answering.
Most tools help you understand papers. RunPaper helps you run them.
No account needed for your first upload. Sign in when you're ready for unlimited access.