ml-paper-writing

To draft an ML research paper safely, generate a narrative-first outline and verify every academic citation programmatically using APIs like Semantic Scholar and arXiv, inserting explicit placeholders if verification fails.

The best way to structure an ML paper for NeurIPS or ICML is to build a complete narrative-first outline, drafting sections iteratively from abstract through limitations while aligning with venue formatting requirements.

Yes, you can draft with unverified citations by using an explicit placeholder pattern during initial writing, but you must complete programmatic citation verification via external services before finalizing the manuscript.

Yes, this ML paper writing workflow supports venue-aware formatting and section structuring for ACL and AAAI, alongside NeurIPS, ICML, ICLR, and COLM, while routing systems venues like OSDI to specialized workflows.

To write the limitations section for an AI conference paper, follow the narrative-first draft plan to explicitly identify and articulate model and experimental boundaries, iterating with feedback to ensure methodological transparency.

You should not use this automated paper drafting workflow for systems research venues like OSDI, NSDI, ASPLOS, or SOSP, as it is specifically tailored for ML and AI conferences and explicitly routes systems papers elsewhere.