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 like hallucinated citations or missing NeurIPS checklist items cause desk rejections. ## Core Features & Use Cases - Full Research Lifecycle Pipeline: Covers project setup, literature review, experiment design, execution monitoring, statistical analysis, drafting, self-review, and submission for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM. - Verified Citation Workflow: Fetches BibTeX programmatically via Semantic Scholar, CrossRef, and arXiv APIs instead of generating citations from memory, with a mandatory 5-step verification process. - Venue Templates & Checklists: Ships official LaTeX templates for six conferences plus pre-submission checklists covering page limits, limitations sections, and LLM disclosure rules. - Use Case: A researcher with experimental results asks the agent to draft an ICML submission; the skill maps claims to experiments, builds the experiment log, writes the LaTeX draft using the icml2026 template, and runs a simulated reviewer pass before submission. ## Quick Start Ask the agent to help write a research paper from your existing codebase and results, specifying your target venue such as NeurIPS or ICML.