Skill UI

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.

This guide provides essential instructions for authors submitting research to the ECAI conference, focusing on creating credible and reproducible artifacts. It strongly cautions authors about misconceptions regarding separate artifact badges, emphasizing that credibility must be built into the paper and supplement for direct reviewer judgment. Guidelines are provided for matching the artifact (code, proofs, data) to the specific contribution type (Theory, ML, Optimization).

This guide outlines best practices for structuring academic papers submitted via OpenReview, particularly for venues like ICLR. It advises authors on where to place different types of evidence—such as core claims, full derivations, code, and large datasets—to ensure the central argument remains visible while maintaining academic rigor. It covers strategies for managing annexes, maintaining anonymity, and updating revisions.

Provides comprehensive guidelines for packaging supplementary materials, including code, data, model weights, and benchmarks, for major machine learning conferences like ICML. It details the requirements for both the double-blind review stage (focusing on anonymization and minimal replication commands) and the final public release package (ensuring permanent public links and clear licensing).

This guide outlines the proper placement of various research materials—including proofs, code, and extended results—within major academic conference submissions. It helps authors understand which content must be presented in the main body, which belongs in appendices, and how to correctly manage supplementary manuscripts and code/data supplements to maximize the chance of reviewer acceptance.

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.