Skill UI

This skill provides comprehensive tools for AI engineers and researchers to publish, manage, and link research papers directly on the Hugging Face Hub. It supports creating dedicated paper pages, linking papers to corresponding models and datasets, claiming authorship, and generating professional, markdown-based research articles with LaTeX support. Use it to streamline the entire academic publishing workflow from initial draft to final publication.

This guide provides a detailed walkthrough of the AAMAS peer review process. It covers everything from initial submissions and technical evaluation (correctness, significance, rigor) to the rebuttal phase, area-chair synthesis, and final decisions. Use this when planning academic submissions or understanding the rigorous criteria for publishing multi-agent systems research.

A comprehensive guide for ML research groups planning multi-venue conference submissions (e.g., COLM). It details the critical path of academic publishing, emphasizing backward induction from hard deadlines (abstract, paper, rebuttal, decision). The workflow covers compute budget allocation, co-author coordination, claim tracking, and managing the technical pipeline from initial topic selection to final presentation, ensuring reproducibility and timely execution in fast-paced AI research cycles.

A comprehensive guide for authors submitting their final, camera-ready version of an accepted EMNLP paper. It details the critical, multi-stage process, including merging reviewed edits, restoring author identity and public links, verifying Anthology metadata, and publishing associated artifacts. This ensures the manuscript meets all strict academic publishing and technical standards.

A comprehensive style guide and checklist for writing and refining long-form academic articles for 'Pattern Recognition and Artificial Intelligence' (PR&AI). It covers the entire publishing workflow, from mastering the structured introduction (Problem-Gap-Contribution) and writing four-element abstracts, to adhering to rigorous standards for citations (GB/T 7714), figures, and mathematical notation in AI research.