Skill UI

This guide helps researchers transform raw empirical findings into portable, discipline-level theoretical contributions suitable for top-tier sociology journals like AJS. It structures the argument by defining core concepts, articulating causal mechanisms, setting scope conditions, and ensuring the theoretical move is generalizable beyond the initial case study.

This guide details best practices for ensuring scientific rigor and reproducibility in complex system research. It outlines the necessity of capturing the full execution state—including hardware steppings, BIOS revisions, kernel configurations, toolchain versions, and dataset provenance—to prevent data decay and validate findings against environmental drift.

This guide outlines best practices for designing and executing Computer Aided Verification (CAV) empirical evaluations. It emphasizes ensuring evidence matches claims by using standard, pinned benchmark sets, selecting fair baselines, respecting equal resource limits, and employing rigorous reporting methods like cactus and scatter plots to establish technical soundness and performance.

This guide provides detailed protocols for achieving high levels of reproducibility in Computer Aided Verification (CAV) research. It emphasizes the necessity of pinning benchmark sets, recording exact tool versions, documenting resource limits (time/memory), and providing checkable proof witnesses to ensure that evaluation claims can be independently validated by competitors or reviewers.

This guide details the necessary steps for converting an accepted CoRL conference paper into its final, permanent PMLR record. It covers mandatory format changes, including expanding to a 9-page main text, merging the appendix, and de-anonymizing author identities. Crucially, it outlines how to manage and link required external artifacts (code, video, datasets) that cannot be hosted by the conference proceedings, ensuring the work maintains an archival standard.

A comprehensive guide for authors preparing manuscripts for CSCW submission. It covers critical pre-upload steps including verifying the current submission pathway, adhering to single-column ACM templates, managing word length scrutiny, ensuring full anonymity (author and setting), confirming ethics statements, and mitigating common desk-risk pitfalls before final submission.

A comprehensive guide for authors preparing the final, camera-ready version of a CVPR accepted paper. It details the multi-channel publication requirements (CVF open access, IEEE Xplore), the necessary steps for de-anonymization, ensuring timely dataset release, optimizing presentation formats (Oral, Poster), and conducting rigorous quality assurance checks before final submission.

A deep dive into the best practices for drafting the Related Work section for top-tier NLP conferences (like EMNLP). This guide instructs authors on how to trace task lineage, verify dataset ancestry, manage concurrent work citations (arXiv vs. Anthology), and ensure rigorous citation hygiene to withstand expert reviewer scrutiny.

This guide provides a comprehensive model of the academic review process used at FAccT. It details the interdisciplinary nature of the review panel (CS, law, social science), the OpenReview workflow, and the strategic implications of the 'Accept/Revise/Reject' decision set. It guides authors on navigating the stages, including rebuttals and revise-and-resubmissions.

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.

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 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.