What problem does it solve? Writing a publication-ready ML/AI paper involves coordinating literature review, experiment design, statistical analysis, LaTeX drafting, citation verification, and venue-specific submission requirements. This Skill provides a structured pipeline that keeps every experiment tied to a paper claim and prevents common failure modes like hallucinated citations and missing conference checklists. ## Core Features & Use Cases - Full Research Lifecycle: Covers project setup, iterative literature search, experiment design with claim-to-experiment mapping, execution monitoring, statistical analysis, drafting, self-review, and submission for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM. - Citation Verification Workflow: Enforces programmatic BibTeX retrieval via Semantic Scholar, CrossRef, and arXiv APIs with a mandatory 5-step verification process to eliminate fabricated references. - Venue Templates & Checklists: Ships official LaTeX templates and mandatory checklist requirements (NeurIPS 16-item checklist, ACL Limitations section, ICLR LLM disclosure) to avoid desk rejection. - Use Case: A researcher with experimental results in a codebase asks the agent to draft an ICML submission; the Skill builds an experiment log, verifies all citations via DOI content negotiation, generates booktabs tables and colorblind-safe PDF figures, and runs a simulated reviewer pass before submission. ## Quick Start Use the research-paper-writing skill to turn my experiment results in this repository into a draft NeurIPS paper with verified citations and submission checklist.
