Skill UI

A comprehensive audit checklist designed for authors submitting data-engineering systems papers to major conferences like ICDE. It covers critical areas including IEEE formatting standards, round selection strategy, Microsoft CMT conflict declarations, and the requirement for supplemental material, ensuring authors mitigate common desk-reject risks.

A comprehensive guide for authors preparing submissions for ICDE conferences. It details how to properly segment content into the main 12-page body versus the supplementary material, ensuring the core argument remains self-contained while providing reviewers with runnable artifacts, extended experiments, and full technical documentation.

A comprehensive guide for authors preparing submissions for top-tier data mining conferences (e.g., ICDM). It emphasizes the critical strategy of preemptively addressing potential weaknesses—such as baselines, variance, scaling, and data leakage—directly within the submitted manuscript, as author rebuttals are often not permitted. Also provides strict guidelines for drafting anonymous, high-impact responses if a rebuttal window is available.

A comprehensive guide for revising technical manuscripts intended for premier data mining conferences like ICDM. It teaches authors to shift focus from model-centric claims to data-regime-first narratives, emphasizing measurable evidence, mechanistic detail, and adhering to strict academic constraints (e.g., triple-blind format, page limits).

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.

Provides strict guidelines for writing the Related Work section in theoretical database papers. It teaches authors how to precisely position their novel results against existing theorems (ICDT/PODS canon), covering complex topics like finite model theory, query complexity, and proper academic citation etiquette, ensuring genuine novelty is highlighted.

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.

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.

This guide details the process of packaging artifacts for academic conferences (ICLR), ensuring that research claims are fully reproducible and reviewable. It emphasizes providing minimal reproduction paths, maintaining data provenance, rigorously anonymizing metadata to protect authors' identities, and creating robust, permanent records for the scholarly community.

A comprehensive self-auditing guide designed for authors preparing manuscripts for submission to top-tier academic journals. It systematically addresses recurring, structural, and critical flaws across theory contribution, econometric identification, mechanism explanation, heterogeneity analysis, and writing conventions. This tool helps authors proactively identify and correct potential weaknesses before facing peer review.

This skill provides comprehensive guidance for authors seeking to submit manuscripts to the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). It helps evaluate the fit of research in signal processing, speech, audio, and image processing. It guides the framing, required empirical evidence (mathematical models, reproducible validation), and optimal positioning of the paper to maximize acceptance chances.

A comprehensive guide for authors submitting data mining research to elite computer science venues like ICDM. This skill helps define the paper's fit, target the correct scope (algorithms, graph mining, etc.), and structure the manuscript to meet rigorous academic standards. It emphasizes providing sufficient evidence, rigorous baselines, and clear positioning relative to the conference's focus.