Skill UI

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 targeting top-tier systems and control journals, such as IEEE Transactions on Automatic Control (TAC). It helps authors evaluate the fit of their manuscript, transitioning from application-heavy case studies to general, provable theoretical theorems with rigorous mathematical proofs and explicitly stated assumptions. Essential for manuscript re-framing and academic submission readiness.

A comprehensive guide for authors on how to position their computational or methodological contributions when submitting to the INFORMS Journal on Computing (IJOC). It emphasizes the critical need to advance against two distinct frontiers simultaneously: the Operations Research/Mathematical Science problem domain, and the core computing methodology. Use this when reviewer feedback questions the novelty or when your work straddles OR and CS boundaries.

This comprehensive guide outlines the necessary theoretical rigor for algorithms and models submitted to top-tier computational journals. It instructs authors on how to formally state mathematical formulations, rigorously prove model validity, establish convergence, and quantify complexity (e.g., approximation ratios, finite termination). It provides specialized paths for exact methods, metaheuristics, and ML-enhanced OR, ensuring that the theoretical advancements fully support and rationalize the experimental findings.

Provides comprehensive guidelines for conducting rigorous networking evaluations, particularly for top-tier conferences. It mandates that every networking claim—be it optimality, performance improvement, or real-world behavior—must be matched with specific, verifiable evidence. This includes rigorous mathematical proof, seeded simulation results, or real-traffic testbed measurements. The guide emphasizes stating assumptions, using fair baselines, and ensuring statistical reproducibility across all studies.

This skill provides a comprehensive assessment tool for authors targeting top-tier pure mathematics journals, such as Inventiones Mathematicae. It guides authors on the required level of mathematical rigor, novelty of argument, significance to the broader research community, and adherence to specific house styles (e.g., LaTeX structure, introduction writing). Use this resource to evaluate whether a strong pure mathematics manuscript meets the exceptional standards of elite academic publishing venues.

This guide clarifies what constitutes an 'artifact' for pure-theory venues like ITCS. It emphasizes that the core deliverable is not code or functional components, but the mathematical argument itself. Successful evaluation relies on providing complete, self-contained proofs within the submitted PDF, along with citing dependencies precisely. It details how to handle minor computational content to ensure static, verifiable checks.

A guide for authors submitting to theoretical computer science venues (ITCS). It strictly defines what constitutes valid evidence for a mathematical claim, emphasizing that complete proofs are paramount. The guidelines detail how to use worked examples, separating objects, and appropriately scoped computations, while strongly advising against using empirical benchmarks or performance metrics.

This guide outlines the standards for making pure theoretical claims independently verifiable. It demands complete, self-contained proofs for all central lemmas, explicit definitions for every symbol, and precise citation for all borrowed results. It ensures that the submitted paper, the full preprint version, and the mathematical arguments are perfectly consistent, addressing the highest level of academic rigor in theoretical computer science.

This guide provides a structured methodology for translating highly technical academic papers, particularly in econometrics or macroeconomics, into plain language suitable for a broad scholarly audience (like the Journal of Economic Perspectives). It focuses on removing notation, jargon, and complex mathematical derivations, while rigorously preserving the underlying economic intuition and causal mechanism of the research.

A guide on how to present highly convincing empirical evidence in academic writing, especially in economics, when regression tables or complex math are limited. This skill teaches readers to translate statistical findings into clear, impactful prose by focusing on magnitude in plain units, synthesizing the body of evidence, defining ranges of precision, and maintaining intellectual honesty.

This guide provides a rigorous framework for constructing formal academic models, tailored for top-tier management journals. It emphasizes the four essential components—decision variables, constraints, objective functions, and assumptions—while providing detailed guidelines on ensuring model completeness, mathematical solvability, and, most critically, the defensibility of every assumption against academic scrutiny.