ml-paper-writing

To draft publication-ready ML papers from a research repository, apply narrative-driven structure guidance to your code and results. This process transforms repository artifacts into formatted text using the What/Why/So What principle and conference-specific templates.

The Narrative Principle for structuring machine learning papers requires clearly presenting a 1-sentence contribution (What), supporting evidence (Why), and real-world impact (So What). This framework ensures your introduction and abstract align with major conference submission guidelines.

Generate reproducibility and citation workflows for conference submissions by applying automated checklists, BibTeX generation, and placeholder-citation handling. This prevents citation hallucinations and ensures your methods and experiments sections meet policy-guided compliance standards.

Yes, this writing guidance supports comprehensive templates and references for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM. It provides formatting, ethics, and broader impact guidance to ensure your manuscript meets specific conference requirements.

Yes, you can convert code and experiment notes into abstract and related work sections by transforming research repository artifacts. The process applies policy-guided templates to draft these sections while maintaining reproducibility and handling placeholder citations.

Prevent citation hallucinations when drafting related work from repository notes by using placeholder-citation handling and verification workflows. This ensures all generated BibTeX entries and references are validated before finalizing the conference submission.