research-paper-writing

Writing an AI research paper for top conferences involves a pipeline of literature review, experiment design, paper drafting, and submission preparation. This Skill provides an end-to-end automated workflow to streamline iterative refinement for venues like NeurIPS, ICML, ICLR, and COLM.

Automating experiment design and analysis for academic writing requires executing experiments and processing data with libraries like scipy and numpy. This Skill automates the execution and analysis steps, utilizing matplotlib and SciencePlots to generate publication-ready visualizations for your research.

Performing an automated literature review using arxiv and Semantic Scholar involves querying APIs to search, verify, and organize relevant papers. This Skill integrates these dependencies to efficiently retrieve and manage academic references throughout your research pipeline.

You need Python dependencies like semanticscholar, arxiv, habanero, scipy, and numpy for text analysis and experimentation. LaTeX document processing is also required for paper writing and submission preparation, ensuring your research output meets top AI conference formatting standards.

This workflow is optimized for iterative paper revision and collaboration in academic settings. It supports structured templates and automated refinement processes, allowing researchers to continuously improve paper quality before submitting to high-level AI conferences.

Citation management and paper verification are handled through the habanero and requests dependencies, which interface with academic databases. This Skill ensures your literature review accurately verifies and organizes relevant papers for your AI research manuscript.