research-paper-writing

Streamline AI research paper writing by covering the full research lifecycle from experiment design and execution to analysis and drafting. This targets top ML conferences like NeurIPS, ICML, and ICLR, supporting iterative feedback loops for continuous paper refinement.

Manage citations and literature search for a machine learning research paper using integrated external APIs. The Skill utilizes Semantic Scholar, arXiv, and Habanero to automate reference management, pulling academic sources directly into your drafting pipeline.

Yes, you can use Python scientific libraries for data analysis and visualization in your research paper. The environment supports Scipy, NumPy, Matplotlib, and SciencePlots to execute experiments and generate publication-ready plots for your analysis.

The best way to draft a structured research paper from initial experiment ideas is running the write_paper command with your research concepts. This generates a structured draft, handling the iterative pipeline of experiment design, analysis, and paper revision.

Yes, you need API access to automate the research lifecycle for conference publication. The Skill requires external API connections for citation management, literature search, and collaboration tools to fully support the end-to-end submission process.

Yes, this research paper writing process supports iterative refinement and collaboration. It handles iterative feedback loops for experiment design, analysis, and paper revision, integrating with collaboration tools to refine drafts before final AI conference submission.