Skill UI

This guide helps structure academic manuscripts by transforming raw findings into clear theoretical arguments, explicit constructs, and falsifiable hypotheses. It provides specific frameworks for both substantive opinion/communication papers and rigorous survey-methodology papers, ensuring the contribution has a clear, testable claim.

This comprehensive guide outlines the requirements for submitting computational artifacts for post-acceptance evaluation at PPoPP. It details PPoPP's unique badge policy (Functional, Reusable, Results Reproduced), addresses the challenges of ensuring results reproduce across different hardware architectures, and provides a detailed packaging plan, including containerization, README structure, and provenance documentation for maximizing reproducibility.

This guide details the strategic process for writing a constrained, data-driven rebuttal for competitive academic conferences (such as PPoPP). It teaches authors how to structure responses to address scaling questions, compare results against baselines, correct factual misreadings, and maximize impact within strict word and time limits. Focus on evidence, not argument.

A comprehensive guide for researchers detailing how to structure the 'Related Work' section for top-tier parallel computing conferences like PPoPP. It emphasizes 'delta-first' comparison, covering specific technical lanes (concurrent data structures, runtimes, GPU acceleration, memory models), and ensuring proper academic positioning against major parallel systems venues.

This guide helps researchers structure their academic papers for the PPoPP conference. It outlines the principle of 'decision-criticality,' advising authors to keep core correctness arguments, headline scaling curves, and design insights in the main body, while moving bulk data, full proofs, and extensive sweeps to the artifact or appendix.

A structured framework designed for authors writing comprehensive psychological reviews or theoretical statements. It guides users to transform a collection of research papers into a single, cohesive, and provocative argument by imposing a unifying structure—such as a taxonomy, theoretical model, or question sequence—that defines the field's central claim.

A comprehensive guide for researchers preparing submissions to specialized academic journals, such as Perspectives on Psychological Science (PoPS). This guide details the strategic process of writing a proposal, differentiating between stand-alone, cooperative, and miscellaneous contributions. It teaches authors how to structure the core argument (the 'spine') and articulate the field's current need, ensuring submissions are timely, focused, and methodologically sound.

A comprehensive guide for revising scholarly 'Perspective' papers after receiving major or minor revisions from editors and reviewers. It provides a structured methodology for addressing common critiques, including coverage gaps, balance complaints, argument strengthening, and open science requirements. This skill helps authors draft a professional, point-by-point response letter and ensures the revised manuscript meets rigorous academic standards.

This guide helps polish and restructure academic manuscripts intended as 'perspectives.' It moves writing beyond simple summary by emphasizing a broad, provocative, and highly accessible voice for non-specialists. It ensures the article follows a specific narrative arc: framing the question, stating the claim early, maintaining signposting, and concluding with a concrete, future-facing agenda.

This guide teaches how to structure the "Related Work" section for top-tier AI journals, focusing on demonstrating the novel incremental contribution (delta) rather than simply listing existing literature. It covers positioning the work within ML/CV/NLP, defining novel problem dimensions, and structuring rigorous comparison tables to withstand external review scrutiny.

This skill serves as the central orchestrator dashboard for authors submitting manuscripts to PR&AI (Pattern Recognition and Artificial Intelligence). It meticulously outlines the entire publication lifecycle, from initial topic selection and structured writing to experimental design, rigorous self-review, navigating peer review stages (initial, expert, final), addressing revisions, and preparing the final camera-ready submission. It breaks down the academic process into actionable stages and critical milestones, ensuring no crucial step is overlooked during the 6-month review cycle.

A comprehensive style guide and checklist for writing and refining long-form academic articles for 'Pattern Recognition and Artificial Intelligence' (PR&AI). It covers the entire publishing workflow, from mastering the structured introduction (Problem-Gap-Contribution) and writing four-element abstracts, to adhering to rigorous standards for citations (GB/T 7714), figures, and mathematical notation in AI research.