Skill UI

A comprehensive guide for academic researchers detailing how to achieve and disclose full reproducibility for Computer Vision and deep learning models. Covers essential practices such as protocol pinning for foundation models, detailed logging of datasets, hardware specifications, and variance honesty, ensuring results remain verifiable years after publication.

This guide provides comprehensive standards for designing, executing, and reporting systems experiments for top-tier academic venues (like ICDE). It emphasizes methodological rigor, including mandatory ablation studies, reporting variance and tail latency (p99), demonstrating scaling trends (curves over points), disclosing cost trade-offs, and ensuring full hardware and software reproducibility to withstand adversarial review.

This guide outlines comprehensive standards for scientific reproducibility in data engineering. It details best practices for pinning hardware, software, datasets, and variance protocols, ensuring that all performance claims are verifiable and re-runnable by peers, making reproducibility a scored component of academic submission.

Provides comprehensive guidelines for packaging and documenting complex robotics research artifacts (code, simulations, hardware designs, datasets, etc.) for scholarly review. It outlines best practices for ensuring reproducibility, adopting the "five-minute-skeptic standard," and managing the full lifecycle of artifacts from review submission to public acceptance.

This guide outlines the rigorous standards for achieving robust reproducibility in robotics research papers, especially those involving physical hardware. It details a two-tier approach, defining results as either fully *rerunnable* (code/simulation) or fully *auditable* (hardware logs/protocols). Key requirements include creating comprehensive hardware specification ledgers, logging detailed sensor data (rosbags), separating deterministic from stochastic claims, and structuring the entire repository for peer review.

A comprehensive guide for authors aiming to submit robotics and automation manuscripts to the IEEE ICRA. It provides detailed advice on conference fit, necessary evidence (hardware/simulation), paper framing, and structuring the work to meet the standards of top-tier robotics venues. It also helps differentiate ICRA from similar conferences like IROS and RSS.

A comprehensive guide for positioning computer architecture manuscripts for the IEEE HPCA conference. It covers ideal scope (accelerators, memory systems, interconnects), required evidence (benchmarks, performance/energy tradeoffs), and strategic framing needed to appeal to top-tier hardware reviewers. Use it to refine your narrative and ensure your contribution meets the high standards of high-performance computing research.

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 skill guides authors on aligning their research manuscript with the scope and standards of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). It provides comprehensive advice on topic fit (e.g., embodied systems, perception, manipulation), structuring the argument for conference reviewers, and detailing necessary evidence (e.g., hardware, simulation, failure cases, system integration). It serves as a strategic tool for advanced robotics conference submission planning.

A comprehensive guide to designing rigorous, reproducible, and fair experimental protocols for computational science research, particularly for top-tier academic journals. It covers critical elements such as selecting standard benchmark instances, establishing strong baselines, ensuring fair parameter tuning, reporting hardware constraints, and performing robust statistical validation, helping researchers avoid common pitfalls and maximize the scientific validity of their claims.

A comprehensive guide for authors submitting computer architecture papers to ISCA. It details the scope fit, required evidence (simulation or hardware), effective framing strategies, and provides comparisons with similar top-tier venues (like MICRO, HPCA). It helps authors refine their manuscript to meet the rigorous standards of a flagship conference.

A comprehensive guide for researchers submitting to major speech conferences (like INTERSPEECH). It details how to harden the reproducibility of speech results, covering crucial 'decay channels' such as corpus versions, text normalization rules (WER), objective metrics (EER), subjective protocols (MOS), and model stochasticity. The guide emphasizes pinning specific toolkits, commit hashes, configurations, and hardware details to ensure scientific rigor and verifiability.