Skill UI

A comprehensive guide for preparing scholarly manuscripts involving spatial data. It outlines best practices for documenting data provenance (sources, projections, processing chains), ensuring reproducibility, and adhering to critical ethical standards such as geoprivacy and human-subjects protection. Essential for maintaining research integrity in academic publishing.

This tool serves as an orchestrator for manuscripts submitted to the Annals of the AAG. It guides authors through the complex submission process by helping define the appropriate academic area (e.g., Human Geography, Physical Geography), the article format (Article, Commentary), and the sequential developmental stages—from topic selection and theory building to data analysis and final submission. It ensures the work is framed legitimately as *geography*.

This guide assists in polishing and formatting academic manuscripts for high-level geographical journals. It ensures adherence to specific academic standards, such as the Chicago Manual of Style (author-date), managing strict word count caps, and structuring the argument to be legible to a broad, interdisciplinary audience. It focuses on elevating prose from subfield jargon to broadly readable academic discourse.

This skill provides authors with a comprehensive guide to positioning their computer science manuscript for the AAAI/ACM Conference on AI, Ethics, and Society (AIES). It covers critical aspects such as framing the contribution, meeting evidence standards, addressing social impacts, and distinguishing the work from similar venues like FAccT. Use it to refine submissions focused on AI ethics, governance, and socio-technical methods.

This comprehensive guide provides authors with best practices for preparing supplementary artifacts for AAAI submissions. It outlines how to structure technical appendices, package reproducible code and data ZIPs, maintain strict anonymity (by removing author metadata and paths), and maximize the evidence for reproducibility. The goal is to ensure that external reviewers can easily verify the research claims without specialized or private tools.

This guide provides a strategic framework for drafting highly effective and concise author rebuttals for major AI conferences like AAAI. Given strict character limits, no URLs, and no new results, it teaches authors how to triage reviewer feedback, focus on decision-critical factual errors, and maximize impact to improve paper acceptance chances.

A comprehensive guide for preparing accepted research papers for final submission to major conferences (e.g., AAAI Press). This process covers strict template adherence, deanonymization of author details, managing copyright transfer, optimizing page counts (including purchasing extra technical pages), and ensuring all source files (LaTeX/Word, figures, bibliography) are correctly formatted for professional publication.

A comprehensive guide for positioning AI/ML manuscripts for top-tier general AI conferences like AAAI. It helps authors refine their scope, frame their contribution, provide necessary evidence (e.g., ablations, baselines), and strategically compare their work against related research and similar venues (ICML, IJCAI). Ideal for pre-submission manuscript refinement.

This skill provides comprehensive guidance for authors targeting the AAAI Conference on Human Computation and Crowdsourcing (HCOMP). It helps authors strategically frame, position, and strengthen the evidence of manuscripts focused on crowdsourcing, human-AI collaboration, and collective intelligence, ensuring the work meets the specific academic bar of the venue.

Provides comprehensive guidelines for designing, auditing, and documenting empirical evidence for high-level AI research submissions (e.g., AAAI). It covers essential methodologies including strong baselines, single-factor ablations, robustness testing (shift, seed, prompt), statistical significance, and ensuring perfect alignment with reproducibility checklists and ethical reporting. Use this guide before submission to ensure empirical evidence strongly supports all claimed AI contributions.

This guide provides a comprehensive pre-submission audit checklist for AAAI conference technical papers. It covers crucial aspects like double-blind anonymity, page limits, reproducibility requirements, author policies, and adherence to the latest AI-use guidelines. Use this before submitting to mitigate risks of desk rejection or policy violation.

This guide provides detailed rules for structuring supplementary material (technical appendices, code/data ZIPs, multimedia) for AAAI submissions. It emphasizes that core contributions and essential evidence must reside in the main paper, while appendices should only deepen the argument. It covers guidelines for maintaining double-blind anonymity, ensuring immutability, and achieving reproducibility.