What problem does it solve? Writing a publication-ready ML/AI paper involves coordinating experiments, verified citations, statistical analysis, LaTeX formatting, and venue-specific checklists, and mistakes in any step cause desk rejections or hallucinated references. ## Core Features & Use Cases - Full Research Lifecycle: Covers project setup, literature review, experiment design, execution monitoring, statistical analysis, drafting, self-review, and submission for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM. - Citation Verification Workflow: Fetches BibTeX programmatically via Semantic Scholar, CrossRef, and arXiv APIs instead of generating citations from memory, marking unverifiable ones as placeholders. - Venue Templates and 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 asks the agent to draft an ICML submission; the skill produces a LaTeX draft grounded in an experiment log, with verified citations, error bars, and the broader impact statement. ## Quick Start Ask the agent to help write a research paper from your experiment results, specifying the target venue such as ICML or NeurIPS.