Skill UI

Guides researchers through drafting publication-ready machine learning papers for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM by combining expert writing philosophy with LaTeX templates, citation verification APIs, and collaborative workflows.

Denario orchestrates a multi-agent AI to automate research workflows, covering idea generation, methodology development, computational experiments, and LaTeX publication output.

Use Nano Banana 2 plus Gemini 3.1 Pro Preview to iteratively craft publication-quality scientific schematics—neural nets, pathways, or system diagrams—matching document-type quality thresholds.

This skill provides comprehensive tools for AI researchers and engineers to publish, index, and manage academic papers directly on the Hugging Face Hub. It supports automatic arXiv indexing, linking papers to specific models and datasets, verifying authorship, and generating professional, markdown-based research articles. It streamlines the entire scientific publication workflow from creation to professional publication.

Transforms vague research directions into highly concrete, elegant, and frontier-aware methodological plans. This skill guides users through an iterative, multi-phase refinement process, ensuring the final output maintains a strong Problem Anchor, focuses on minimal adequate contributions, and is ready for top-tier academic publication.

Generates structured peer-review quality critiques of academic papers, covering summaries, methodology scrutiny, contribution evaluation, literature positioning, and recommendations across domains whenever a user requests reviews, analyses, or summaries of research publications.

A powerful AI tool designed to transform complex scientific concepts into publication-quality visual schematics. Utilizing Nano Banana 2 AI for generation and Gemini 3.1 Pro Preview for rigorous quality review, the skill specializes in creating architectural diagrams, neural network structures, biological pathways, and complex flowcharts. It employs smart iterative refinement, ensuring the output meets predefined quality thresholds for academic journals, posters, and reports.