Skill UI

A comprehensive guide to the rigorous, multi-stage peer review process for top-tier data engineering conferences like ICDE. It details the two-round structure, area-chair coordination, single-blind dynamics, and the high standards set by 'builder-heavy' reviewers. Use this to strategize paper submission, understand key evaluation dimensions (novelty, soundness, evaluation), and anticipate common review objections.

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 outlines the professional and technical process for authors responding to peer reviewers after a major conference submission (e.g., ICDT). It emphasizes that the revision must be a substantive correction—closing all identified proofs gaps, clarifying models, and documenting changes—rather than a mere argument or debate over taste. It provides a structured, point-by-point approach for maximizing the chances of acceptance.

This guide provides rigorous guidelines for structuring theoretical papers submitted to the International Conference on Database Theory (ICDT). It emphasizes that proofs and formal evidence are the primary contribution, not benchmarks or experiments. It teaches authors how to match their specific theoretical claims (e.g., complexity, expressiveness) to the appropriate academic evidence, ensuring that any proposed experiment is proportional, honest, and merely supplements the core theoretical results.

This guide outlines the standards for ensuring the verifiability and rigor of theoretical computer science papers, particularly for venues like ICDT. It mandates complete proofs, precise pinning of models and assumptions, explicit matching of upper and lower bounds, and strict internal consistency across all claims and full versions. Use this checklist before submission to elevate academic quality.

Details the rigorous, structured review process for ICDT (International Conference on Database Theory). The model emphasizes that referees scrutinize proof correctness, not just novelty. It guides authors through the two-cycle submission process, explaining the strategic implications of Accept, Revise, and Reject decisions to ensure deep theoretical foundations.

A comprehensive audit guide for authors preparing submissions for the International Conference on Database Theory (ICDT). This guide covers critical aspects including selecting the correct submission cycle, adhering to the two-step abstract-then-paper deadline, meeting the LIPIcs formatting standards (15 pages excluding references), ensuring complete and verifiable proofs, and maintaining strict anonymity since 2024. Use this before uploading to Microsoft CMT.

This guide provides strict guidelines for structuring technical conference papers, especially when supplementary proofs are required. It emphasizes the critical rule that the main body (typically 15 pages) must be self-contained and sufficient for a referee to judge the result's significance, even if they do not read the marked appendix. It strictly forbids external links or online supplements for review.

This guide helps researchers decide the most appropriate venue for their database theory research, comparing major conferences like ICDT, PODS, EDBT, and top journals (ACM TODS, LMCS). It provides detailed criteria, such as the required data-management consequence, the nature of the theorem, and strategies for choosing between competing flagship venues based on calendar, publisher, and community fit.

A meticulous style guide for authors submitting papers to the International Conference on Database Theory (ICDT). It mandates a rigorous theorem-proof structure, emphasizing precise statement of data models, query languages, and complexity measures. The guide teaches how to structure the introduction to lead with the core result and its data-management implications, adhering to top-tier academic standards.

A comprehensive guide for structuring and polishing scholarly review articles for a broad academic audience. It ensures the writing adopts an authoritative, highly accessible, and forward-looking narrative arc, guiding the author to move beyond mere summary and establish a clear research agenda.

This guide assists researchers in determining the optimal venue for their theoretical machine learning contributions. It provides a framework for evaluating whether a result is best suited for COLT, or if it belongs in other top-tier conferences (e.g., NeurIPS, ICML) or journals (e.g., JMLR). It emphasizes differentiating between rigorous mathematical proofs (bounds, separations) and purely empirical findings.