Skill UI

Guides researchers through drafting publication-ready ML/AI or systems papers for venues like NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, and SOSP; includes LaTeX templates, citation verification workflows, conference checklists, and proactive collaboration steps from repo exploration to camera-ready drafts.

Python toolkit that queries the arXiv Atom API to search papers by keywords, authors, categories, or IDs, filter results, download PDFs, and emit structured JSON for AI/ML literature reviews and monitoring.

Auto-generates publication-quality plots and comparison tables from experiment data, following a shared matplotlib style, respecting figure plans, and preserving manual assets for ML papers.

Produces publication-quality figures for ML/AI conference papers by extracting system components for Gemini-based architecture diagrams and turning experimental data into matplotlib/seaborn charts with auto-selected types, layouts, and highlights so visuals match the paper context.