Skill UI

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 guide for designing and reporting rigorous experimental results in robotics research. It details the 'evidence ladder' (from simulation to real-world deployment), statistical best practices (e.g., sample size, confidence intervals), ensuring baseline fairness, and quantifying sim-to-real transfer gaps. Essential reading for researchers submitting to top-tier robotics conferences.

A comprehensive, single-cycle master calendar and workflow guide for major academic conferences like ICSE. It details the entire ten-month journey, covering mandatory milestones from abstract submission and full paper drafting to author response, revision sprints, and final camera-ready preparation. This guide helps research teams plan backward, mitigate timeline risks, and manage complex project dependencies.

A comprehensive guide for authors targeting the IEEE-RAS International Conference on Humanoid Robots. This skill helps frame, scope, and structure research papers in humanoid robotics. It dictates the necessary level of hardware evidence, whole-body control integration, and perception depth required to succeed at this top-tier venue, while distinguishing it from general robotics conferences like ICRA or RoboCup.

This guide assists authors targeting the IEEE Spoken Language Technology Workshop (SLT) with conference positioning and manuscript re-framing. It provides deep insights into the required scope, evidence bar (e.g., speech-specific deployment, acoustic conditions), and narrative structure needed to successfully submit research in spoken language understanding, dialogue, and speech systems to top-tier CS venues.

This comprehensive guide helps authors strategically position their theoretical computer science manuscript for the IEEE Symposium on Foundations of Computer Science (FOCS). It analyzes the paper's core contribution type, required technical depth (algorithms, complexity, cryptography), necessary evidence, and structural framing to meet the high academic standards of the venue. Ideal for venue selection and manuscript refinement.

A comprehensive guide for authors structuring signal processing manuscripts for top-tier venues like IEEE Transactions on Signal Processing. It details the necessary theoretical depth, the requirement for rigorous analysis (e.g., convergence, bounds), correct baseline selection, and adherence to specific academic formatting. This tool helps authors reframe general machine learning applications into rigorous, theory-driven scientific methods.

This guide outlines the rigorous requirements for building a comprehensive replication package and proof appendix for manuscripts submitted to journals following the International Economic Review (IER) style. It details what must be included in the data deposit (datasets, programs, README) and how to structure a self-contained proof appendix, ensuring the work meets the highest standards of reproducibility and scientific rigor required for publication.

A comprehensive framework for researchers to assess if their AI research contribution is best suited for a major conference like IJCAI, or if a highly specialized venue (such as NeurIPS, ICML, CVPR, or ACL) would provide a clearer audience. It guides decisions based on technical depth, problem scope, and contribution type.

A comprehensive project management skill designed for authors planning submissions to major AI conferences (like IJCAI). This guide outlines the critical milestones, dependencies, and risk checkpoints, guiding the team from initial venue fit through abstract registration, full-paper upload, review responses, and final presentation artifact release. It ensures all deadlines and author requirements are met to maximize acceptance chances.

This comprehensive guide provides best practices for designing, running, and reporting computational experiments for academic journals. It teaches authors how to make performance claims scientifically defensible by addressing potential referee criticisms (e.g., tuning artifacts, seed luck). It covers advanced statistical techniques (performance profiles, nonparametric tests) and details the full structure required for a complete, verifiable GitHub data deposit.

A comprehensive preflight checklist for authors submitting to the INFORMS Journal on Computing (IJOC) via ScholarOne. This guide details critical academic publishing standards, including the 25-page limit, single-blind review rules, required LaTeX formatting, and the mandatory structure for the GitHub code/data reproducibility deposit. Use this when performing the final checks before submission.