Skill UI

A comprehensive guide for structuring academic system evaluation papers (e.g., OSDI). It dictates how to frame experiments around core research questions, select robust baselines, utilize realistic workloads (including adversarial tests), and apply rigorous measurement disciplines (e.g., reporting distributions, p99s) while maintaining conciseness within strict page limits.

This guide provides best practices for designing and auditing academic evaluations of programming language features and compilers, following standards used in venues like PLDI. It covers selecting defensible benchmark suites, establishing strong baselines, performing targeted ablations, and measuring multiple performance metrics (runtime, compile time, memory) to ensure research claims are reproducible and scientifically sound.

A comprehensive guide for assessing the scope and significance of high-quality, cross-disciplinary research. This skill helps authors determine the optimal publishing venue—whether it should be PNAS Nexus, flagship PNAS, or a specialized field journal—by evaluating how broadly the findings resonate across biological, physical, social, and engineering sciences. It is crucial for submissions and for judging transfer opportunities following a PNAS decline.

Provides detailed guidelines for submitting empirical papers to POPL. It teaches authors how to correctly match specific claims (e.g., soundness, precision) with appropriate evidence types (proofs, case studies, effort data). The core principle emphasized is that evidence must demonstrate realizability but never substitute for the formal theorem.

This guide outlines best practices for PRL submissions, detailing how to select suggested and opposed referees. It emphasizes demonstrating both scientific correctness and broad interdisciplinary significance to preempt likely reviewer objections, maximizing the letter's chance of acceptance.

This skill guides authors in assessing whether their scholarly work—particularly those employing New Historicism or interdisciplinary cultural analysis—is suitable for highly specialized academic venues. It emphasizes the necessity of building arguments outward from concrete historical or material particulars (like archival fragments or objects), rather than relying on free-floating theory. Use this aid to re-frame and strengthen the material basis of your scholarly manuscript before submission.

This guide assists in building a robust theoretical framework for research policy manuscripts. It moves beyond simple empirical measurement by structuring the argument using the innovation-mechanism chain (antecedent → mechanism → outcome). It teaches how to connect firm-level findings up to the systemic policy or institutional level, ensuring the contribution is theoretically advanced and legible across disciplines (e.g., economic, managerial, STS).

This skill guides authors through the complex process of selecting the optimal academic journal venue for their research. It profiles the paper's characteristics (discipline, method, contribution) and shortlists potential targets from a large index. It scores candidates based on fit, acceptance odds, turnaround time, and audience, providing a tiered recommendation (Reach, Match, Safe) and a detailed resubmission ladder. Ideal for rejected drafts or papers needing a first target.

This comprehensive guide provides the optimal structure and academic writing discipline for submitting high-quality technical papers to major computer graphics conferences, such as SIGGRAPH. It emphasizes building a compelling 'first-page arc,' leveraging the teaser figure to immediately demonstrate results, maintaining academic honesty by detailing limitations, and adhering to strict page budget constraints.

A specialized guide for structuring the literature review of a sociological methods manuscript. It teaches authors how to position their contribution not against the topic, but against established methodologies. Users learn to map their work against prior estimators, cross-discipline techniques (statistics, econometrics, psychometrics), and competing approaches to maximize academic credibility.

A comprehensive guide for authors transitioning an accepted paper from a full draft to the strict, camera-ready proceedings format required by major conferences like SODA. It covers critical steps such as content compression, de-anonymization (restoring author metadata), adhering to SIAM formatting rules, and establishing proper citation hygiene across multiple versions (proceedings, arXiv, journal).

A comprehensive guide for authors submitting theoretical computer science papers to SODA. It clarifies the distinction between SODA (theory-led) and ALENEX (experiment-led), advising on when and how to incorporate numerical evidence. The protocol details best practices for honest numerics, including instance generation discipline, claim-class labeling (illustration, evidence, motivation), and proper submission routing to ensure academic rigor.