Skill UI

This comprehensive guide outlines the strict requirements for preparing replication and data packages for submission to The Econometrics Journal (EctJ). It covers everything from README structure and detailed code inclusion to ensuring Monte Carlo determinism and managing restricted data, ensuring the method's credibility for reviewers.

This comprehensive preflight checklist guides researchers through the final essential steps before submitting a manuscript to the European Economic Review (EER). It ensures adherence to Elsevier formatting standards, addresses mandatory replication policies (data/code availability), verifies funding declarations, and confirms all necessary fees and ethical statements are in place. Use this guide as the ultimate final check before pressing submit.

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.

This guide outlines the rigorous methodological standards for empirical work in AI fairness, accountability, and transparency (FAccT). It advises researchers on matching specific claims (e.g., disparate harm) to appropriate evidence types—including disaggregated metrics, coded qualitative data, and documented ethical procedures. It stresses the importance of ethical review, handling protected attributes, and acknowledging limitations to ensure high scientific and ethical rigor.

This comprehensive guide provides a structured strategy for handling major scientific manuscript revisions and writing professional rebuttal letters. It instructs authors on how to systematically address every reviewer concern—especially regarding mechanism, scale, uncertainty, and reproducibility—while ensuring the revised manuscript remains perfectly synchronized with the archived data and code.

A comprehensive guide for structuring Human-Robot Interaction (HRI) conference submissions. It outlines the critical distinction between core, decision-making content (which must remain in the 8-page body) and supplementary materials (e.g., extended tables, instruments, codebooks). Special emphasis is placed on treating the video figure as a primary artifact, ensuring it is short, legible, and properly anonymized for double-blind review.

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.

This guide details the best practices for packaging, documenting, and releasing research artifacts (code, models, data) for top-tier ML conferences. It covers two stages: preparing a non-identifiable archive for anonymous review, and managing the public release runway, focusing on reproducibility, licensing, and sustained maintenance.

A comprehensive guide for authors submitting to top-tier computer vision conferences (like ICCV). It details the new single-deadline workflow, emphasizing the parallel production of code and videos. Learn how to structure supplementary materials for maximum reviewer impact, including detailed ablation studies, failure mode galleries, and maintaining strict double-blind anonymity in the archive.

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.

This guide outlines the specific expectations for preparing the 'artifact' when submitting papers to the International Conference on Database Theory (ICDT). It clarifies that ICDT is a pure theory venue, meaning the primary deliverable is not runnable code or system badges, but the complete, verifiable proof. Key components include the marked appendix (for review) and the consistent, archived full version on arXiv.

This guide helps authors structure lengthy academic manuscripts, ensuring the main text maintains a clear, focused narrative while relegating supportive, detailed evidence to the appendices or supplementary materials. It outlines the 'determinative' principle, advising where to place hyperparameters, extended experiments, proof details, and code links to meet high journal standards and maximize readability for reviewers.