Skill UI

A rigorous framework for designing reproducible and scientifically sound experiments in robotics and AI, specifically for academic publication (e.g., RSS). It guides users to shift focus from simple system demonstration to testing a falsifiable scientific claim. Key areas covered include deriving conditions from a claim, establishing hardware trial protocols, managing simulation vs. real-world evidence splits, and performing detailed failure attribution analysis.

This skill provides a detailed framework for researchers to determine the most suitable venue (e.g., RSS, ICRA, CoRL, IROS) for their robotics project paper. It teaches how to shift focus from merely demonstrating a system's capabilities to articulating a precise, testable scientific claim, ensuring the work is optimally presented to the target academic community.

This guide provides a comprehensive project management framework for submitting research to major robotics conferences, particularly RSS. It maps out the complex annual cycle, from abstract submission to final presentation, detailing critical deadlines, required milestones (like hardware trials and writing drafts), and fallback options at sibling venues (IROS, CoRL, ICRA). Essential for researchers managing time-sensitive academic pipelines.

This comprehensive guide provides a rigorous framework for scientific reporting, ensuring statistical integrity and full reproducibility. It instructs authors on essential elements like reporting effect sizes, justifying sample sizes, controlling for multiple comparisons, and distinguishing biological from technical replicates, helping manuscripts meet the high standards of top-tier scientific journals.

This skill guides researchers on assessing if their academic project fits the scope and standards of a major social science journal. It provides a rigorous framework to test for general significance, methodological credibility, theoretical contribution, and adherence to strict word limits, helping authors effectively frame their work for a broad academic audience.

This skill assists researchers in strategically positioning their computer graphics and visualization research. It evaluates whether a contribution is truly "graphics-shaped" (demanding visual results and advancing graphics axes) and recommends the optimal venue (e.g., SIGGRAPH, CVPR, CHI, EGSR) and submission track (Dual-track or Journal-only) based on the nature and maturity of the work. It provides a crucial, high-leverage decision framework before committing to a submission.

This guide provides a comprehensive framework for authors responding to peer reviews in major NLP/IR conferences. It covers strategies for active rebuttal periods, pre-emptive revisions when no window exists, and planning resubmissions after rejection. Key advice includes technical rebuttal tactics (e.g., addressing baselines, significance testing), maintaining professional tone, and efficiently using existing computational evidence to maximize acceptance chances.

This skill provides a comprehensive project management framework for submitting research papers to SIGMETRICS. It guides users through the complex, multi-stage process, including evidence lock, abstract registration, handling rolling deadlines, one-shot revisions, and final publication preparation. It emphasizes backward planning heuristics and mitigating common academic failure modes.

A comprehensive methodological guide for researchers submitting data management papers. It helps users assess if their contribution is a fundamental system advance or merely an application. The guide provides detailed decision frameworks and comparisons between top-tier venues like SIGMOD, PVLDB, KDD, and PODS, ensuring the focus remains on the core data-management primitive.

This guide teaches researchers how to move beyond basic literature reviews by positioning their work within a specific, ongoing scholarly debate. It provides a framework to identify the core scholarly 'conversation,' pinpoint the theoretical gap (mechanism or tension), and articulate a novel move that advances the field's understanding, crucial for high-impact academic journal submissions.

This comprehensive guide provides methodological frameworks for designing rigorous empirical studies in strategic management. It covers defining the sample, selecting the unit of analysis, validating key measures (performance and strategic choices), and critically, implementing robust identification designs (e.g., DID, IV, Fixed Effects) to address endogeneity and establish causal claims.

This guide provides a comprehensive framework for drafting a professional and persuasive response letter to academic journal reviewers following a major or minor revision (R&R). It details the precise structure, from addressing the editor to point-by-point rebuttals, emphasizing how to tackle core concerns like endogeneity and theoretical contribution with evidence, not just rhetoric.