What problem does it solve? Drafting ML conference papers is slow and error-prone: structuring a compelling narrative, meeting strict venue formatting rules, and avoiding hallucinated citations (which have a ~40% error rate when generated from memory) all demand significant effort. This Skill guides the end-to-end paper writing workflow from a research repository to a camera-ready submission. ## Core Features & Use Cases - Structured Paper Drafting: Step-by-step workflows for abstract, introduction, methods, experiments, related work, and limitations, based on writing philosophy from Neel Nanda, Sebastian Farquhar, Karpathy, Lipton, and Steinhardt. - Hallucination-Free Citations: Mandatory programmatic citation verification using Semantic Scholar, CrossRef, and arXiv APIs, with BibTeX fetched via DOI content negotiation and explicit placeholders for unverifiable references. - Conference Templates & Checklists: Official LaTeX templates for NeurIPS 2025, ICML 2026, ICLR 2026, ACL, AAAI 2026, and COLM 2025, plus venue-specific checklists, reviewer guidelines, and format conversion workflows for resubmission. - Use Case: Given a research repository with code and results, produce a complete first draft of an ICML submission with verified BibTeX references, then convert it to ICLR format after rejection while addressing reviewer concerns. ## Quick Start Ask the AI to read your research repository and draft a complete NeurIPS paper using the bundled LaTeX template, verifying every citation through the Semantic Scholar API.