research-paper-writing

To write a research paper for top AI conferences like NeurIPS, ICML, or ICLR, this Skill provides an end-to-end pipeline covering literature review, experiment design, result analysis, and structured writing with templates. It guides you through the full research lifecycle to produce publication-ready papers.

Automate literature review and citation verification for academic writing by utilizing integrated tools like Semantic Scholar and arXiv. This Skill streamlines information retrieval and validates references to ensure your research paper is backed by accurate and relevant citations.

Yes, you can use Python libraries for data analysis and visualization in AI research papers. This Skill requires dependencies like SciPy, NumPy, and Matplotlib, alongside SciencePlots, to run experiments, perform statistical analysis, and generate publication-quality figures.

Yes, you need LaTeX and Git to manage your research paper writing workflow effectively. These dependencies support paper formatting, version control, and BibTeX citation management, ensuring your submission for AI conferences is properly structured and tracked.

The best way to structure an end-to-end AI research experiment pipeline is to follow a structured workflow that iteratively loops through experiment design, execution, result analysis, and writing. This Skill provides templates and guidelines to manage this entire process efficiently.

Limitations of using automated tools for research paper writing include their specific applicability to academic research in AI and related fields. While the Skill manages experiments and retrieves information via arXiv and Semantic Scholar, researchers must still provide the core scientific contributions and domain expertise.