Skill UI

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.

This guide outlines the rigorous standards for achieving robust reproducibility in robotics research papers, especially those involving physical hardware. It details a two-tier approach, defining results as either fully *rerunnable* (code/simulation) or fully *auditable* (hardware logs/protocols). Key requirements include creating comprehensive hardware specification ledgers, logging detailed sensor data (rosbags), separating deterministic from stochastic claims, and structuring the entire repository for peer review.

This guide provides comprehensive best practices for authors submitting software artifacts to academic venues like ICSME. It details how to structure packages, track provenance, and document code to achieve the IEEE Open Research Object and Research Object Reviewed badges. Learn how to design for rigorous, reproducible evaluation by evaluators in a bounded time frame.

A comprehensive preflight checklist for authors submitting to the INFORMS Journal on Computing (IJOC) via ScholarOne. This guide details critical academic publishing standards, including the 25-page limit, single-blind review rules, required LaTeX formatting, and the mandatory structure for the GitHub code/data reproducibility deposit. Use this when performing the final checks before submission.

A detailed guide for authors preparing manuscripts for the IMF Economic Review (IMFER). This checklist ensures compliance with strict academic publishing standards, including double-blind anonymization, proper formatting (Chicago style, JEL codes), and the correct separation of author-identifying information before final submission via Editorial Manager.

This guide outlines best practices for packaging complex research artifacts—including simulators, codebases, and datasets—to maximize credibility and reproducibility. It is essential for authors publishing in venues like INFOCOM where formal artifact evaluation tracks are not mandatory. Learn how to structure your submission to build reviewer trust and ensure your findings can be independently verified.

A comprehensive guide for researchers submitting work to INTERSPEECH. It details how to package and manage various artifacts—including code, audio samples, and trained models—through the conference lifecycle. The document emphasizes maintaining anonymity during review, ensuring scientific reproducibility, managing complex data licenses, and adhering to ethical guidelines for voice data and synthetic media release.

This comprehensive guide details the end-to-end technical program committee (TPC) review process for major academic conferences like INTERSPEECH. It walks through every stage—from initial submission and area assignment to independent review, rebuttal, meta-review, and final decision. Users can learn how to decode reviewer feedback, understand the limitations of the rebuttal, and develop a strategic plan for future submissions and research refinement.

A comprehensive guide for structuring the evidence bundle required for robotics research submissions. It details the critical components—including hardware ledgers, time-stamped logs, configuration files, code, and data—necessary to ensure that scientific claims are fully auditable and reproducible, addressing the needs of skeptical reviewers.

A comprehensive guide for researchers on how to structure, package, and document complex scientific artifacts (e.g., simulation results, specialized code) to ensure reproducibility for academic reviewers. It details setting scope tiers (Reproduce, Regenerate, Inspect) and mitigating technical challenges like build fragility and runtime discrepancies.