ml-paper-writing

# ML Paper Writing for Top AI Conferences Expert-level guidance for writing publication-ready papers targeting **NeurIPS, ICML, ICLR, ACL, AAAI, and COLM**. This skill combines writing philosophy from top researchers (Nanda, Farquhar, Karpathy, Lipton, Steinhardt) with practical tools: LaTeX templates, citation verification APIs, and conference checklists. ## Default operating order Use this skill in the following order unless the task is unusually narrow: 1. lock the operating mode from `references/OPERATING-MODES.md`, 2. understand the repo or draft context, 3. use `references/citation-workflow.md` as the **canonical citation authority**, 4. load venue- or template-specific references only after the main writing path is clear. Google Scholar may still help with manual discovery, but it is **not** the canonical verification authority in this skill. Default verification should use programmatic sources such as Semantic Scholar, CrossRef, and arXiv. ## Claim ledger gate Before a project plan, experiment note, or literature summary becomes manuscript prose: - identify the Claim Candidate or Evidence Record that supports the sentence, - preserve allowed wording and forbidden stronger wording, - keep project plans as hypotheses unless experiment artifacts or verified papers support them, - do not turn related-work motivation into evidence for the paper's own result, - mark unsupported claims as `[CLAIM NEEDS EVIDENCE]` instead of polishing them. If the repo context is clear...