Skill UI

This guide offers advanced methodological advice for structuring the 'Related Work' section for top-tier theoretical computer science conferences (like FOCS). It teaches researchers how to treat research history as 'lineage engineering,' requiring precise citation of specific preprints (arXiv version pinning), distinguishing between conference and journal versions, and transparently addressing concurrent results. This ensures the bibliography is rigorous, consistent, and withstands expert review.

This guide provides a comprehensive overview of the editorial and review process for the Journal of Public Economics (JPubE). It details the single anonymized review model, expectations regarding multiple specialist reviewers, the use of Editorial Manager, and strategic advice for SSRN preprints and appeals. Use this skill when planning a submission, understanding review outcomes, or managing academic publication expectations.

This guide provides a comprehensive framework for positioning theoretical algorithms research in top-tier venues like SODA. It details how to conduct a rigorous "related work" review, covering bound lineages across conference proceedings, journal publications, and arXiv preprints. Learn best practices for citing dual-version results, managing priority claims, and writing scholarly prose to establish your result's state-of-the-art status.

A comprehensive guide for authors writing theoretical computer science papers. It details how to position a result within the existing academic lineage, ensuring rigorous citation practices, managing version discrepancies (preprint vs. journal), and honestly comparing bounds against prior work. Essential for meeting the high standards of top-tier conferences like STOC.