Skill UI

A comprehensive guide detailing the methodology for packaging, documenting, and staging research artifacts (including code, datasets, knowledge graphs, and demo systems) for CIKM conference submission. It covers best practices for licensing, provenance tracking, versioning, and transitioning artifacts from anonymous review status to citable public releases, ensuring reproducibility and adoptability.

This comprehensive checklist guides authors through the final pre-submission review process for demanding academic journals. It ensures the manuscript is scientifically rigorous and complete, focusing on critical areas such as model-driven theoretical advancement, model comparison, data reproducibility (depositing code and verifying fit regeneration), and adherence to open science mandates. Use this guide before uploading to the journal's portal.

This guide details best practices for enhancing the credibility of academic manuscripts submitted to scholarly journals, particularly addressing code and data availability. It teaches authors how to proactively provide stable links, checksums, comprehensive reproducibility scripts, and clear licensing statements. The focus is on bolstering trustworthiness for single-blind review processes, even when the journal does not mandate formal artifact badges.

This guide outlines the creation of a complete, verifiable research package for economic policy manuscripts. It ensures that all empirical, experimental, or simulation results are fully reproducible by providing raw data guides, cleaning scripts, analysis code, and a single 'master' script that runs end-to-end. This process is critical for academic acceptance, allowing reviewers and discussants to independently verify every figure, table, and key number reported in the paper.

A comprehensive guide for researchers on packaging and documenting NLP artifacts, such as datasets, prompts, and evaluation code, for academic publication. It details best practices for ensuring reproducibility, managing provenance, adhering to licensing standards, and structuring evidence for top-tier conferences like EMNLP.

A comprehensive guide detailing the ICASSP peer review pipeline, covering single-blind review mechanics, technical committee evaluation criteria, and the strategic importance of evidence, significance, and reproducibility in signal processing papers. Use this to craft submission strategies and decode decision letters.

Provides comprehensive guidelines for packaging research artifacts (code, data, logs) for submission to data mining conferences like ICDM. The focus is on ensuring the artifact is completely anonymous for triple-blind review (scrubbing Git history, paths, and internal names) and maximizing reproducibility, allowing reviewers to verify results with minimal effort.

Provides comprehensive guidelines for packaging and documenting complex robotics research artifacts (code, simulations, hardware designs, datasets, etc.) for scholarly review. It outlines best practices for ensuring reproducibility, adopting the "five-minute-skeptic standard," and managing the full lifecycle of artifacts from review submission to public acceptance.

This guide assists researchers in assembling a comprehensive, reproducible data and code supplement for submissions to statistical journals, adhering to the American Statistical Association (ASA) data-sharing policies. It outlines the required structure (README, code, data), provenance tracking, environment pinning, and necessary steps (like setting random seeds and drafting data availability statements) to ensure that published results can be fully regenerated and verified by reviewers.

A comprehensive preflight checklist designed for submitting manuscripts to the Journal of Business & Economic Statistics (JBES). This guide ensures authors have verified all necessary components—including the data/code supplement, conflict disclosures, and cover letter targeting—against the latest academic standards. It functions as a critical final review step before formal submission, emphasizing the need to cross-reference live journal guidelines.

This guide provides best practices for preparing code, data, and supporting artifacts for academic submissions, focusing on achieving reproducibility for peer review (especially in double-blind settings). It covers crucial steps including artifact anonymization, establishing clear data availability statements, structuring the repository (README, env, data, src), ensuring licensing compliance, and planning for permanent post-acceptance archiving.

A comprehensive guide for structuring responses to highly selective academic journal reviews, specifically for The Journal of Finance (JF) revise-and-resubmit manuscripts. It details how to prioritize the editor's central concerns over individual referee points, manage the revision process, utilize the Internet Appendix, and adhere to strict journal formatting and code-sharing guidelines.