research-paper-writing

Automate ML paper writing by providing a project prompt to generate a complete draft with an outline, references plan, and submission checklist, integrating literature synthesis, experiment design, and iterative review loops.

Automated literature review and citation management work by integrating with Semantic Scholar, arXiv, and CrossRef to synthesize sources, manage references, and populate publication-ready manuscripts with accurate citations.

Yes, you can use this pipeline for designing reproducible ML experiments and analyzing results, as it integrates experiment tracking, reproducibility artifacts, and numerical analysis using scipy and numpy.

Prepare a research paper for major ML conferences by running the end-to-end pipeline, which handles drafting, iterative revision, formatting, and generates a comprehensive submission checklist for target venues.

Yes, you need specific Python libraries including requests, scipy, numpy, matplotlib, and SciencePlots to execute codebase analysis, run numerical experiments, and generate scientific plots for the manuscript.

Limitations include relying entirely on provided codebases and datasets for experiment execution, requiring manual oversight for iterative review loops, and depending on external API availability for citation retrieval.