Skill UI

This skill guides authors to evaluate if their ecology or biology manuscript meets the rigorous standards of Global Change Biology. It focuses on the necessity of linking research findings to explicit global-change drivers (e.g., warming, elevated CO2) and providing robust biological evidence, from molecular mechanisms to ecosystem-scale consequences.

This guide instructs authors on creating mandatory Data Availability Statements and building comprehensive replication materials for academic manuscripts. It covers best practices for data provenance, code management, and handling restricted data, ensuring research integrity and reproducibility.

This guide details the strategic process of writing a rebuttal for top-tier academic conferences (such as HRI). It provides a framework for triaging reviewer critiques, addressing methodological concerns (e.g., sample size, confounding), and making credible, actionable promises for the final camera-ready version, all while maintaining academic integrity and anonymity.

A comprehensive guide for researchers submitting signal processing papers, detailing how to achieve rigorous reproducibility for conferences like ICASSP. It emphasizes that simply providing a model is insufficient; authors must pin down the 'scoring ruler,' data versions, front-end parameters, and computational seeds to ensure every reported metric can be independently verified.

A comprehensive audit guide for submitting papers to ICASSP conferences. This checklist covers crucial requirements such as the mandatory 4+1 page format, single-blind review rules (including author list inclusion), CMS portal submission protocols, EDICS metadata selection, and compliance with ethical standards. Use this guide before the deadline to avoid desk rejects.

A comprehensive guide modeling the ICCV review pipeline, covering the entire cycle from registration to final decision (March-June). It details author responsibilities, the enforcement of reviewer accountability, the prohibition of LLM use in reviews, and strategies for authors to interpret and leverage diverse review feedback, including utilizing the 'Findings' workshop.

A comprehensive guide for positioning database research papers for top-tier conferences like ICDE. It teaches authors how to distinguish genuine novelty (new mechanisms) from engineering delta (implementation improvements), conduct deep literature audits, and compare their work against both academic venues and real-world production systems. Essential for improving manuscript eligibility and impact.

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.