Skill UI

This comprehensive guide provides best practices for packaging supplemental materials and artifacts for top-tier academic conferences like ICDE. It instructs authors on how to build a robust, reproducible evidence chain, including parameterized workload generators, configuration scripts, and detailed logs. The goal is to ensure that reviewers can quickly and accurately validate all performance claims and technical contributions, making the work 'turnkey' and verifiable.

A comprehensive guide for researchers on how to structure, package, and document complex scientific artifacts (e.g., simulation results, specialized code) to ensure reproducibility for academic reviewers. It details setting scope tiers (Reproduce, Regenerate, Inspect) and mitigating technical challenges like build fragility and runtime discrepancies.

A comprehensive guide for authors revising technical papers for top-tier conferences like ISSTA. It details the necessary structure, emphasizing strict scope definition, establishing clear evaluation contracts (subjects, baselines, metrics), pairing every claim with concrete evidence, and adhering to specialized review discipline.

A comprehensive guide for authors writing ML systems papers for MLSys. It teaches authors how to structure a technical argument by focusing on a measured bottleneck, naming mechanisms, and structuring the evaluation around research questions. It emphasizes numerical discipline, proper figure usage, and conciseness to fit within conference page limits.

A comprehensive tool for authors submitting work on electronic devices, circuits, or systems to Nature Electronics. It guides the evaluation of the manuscript's broad scientific significance, technical rigor, and adherence to Nature's high stylistic and scientific standards, ensuring the work is field-advancing rather than merely incremental.

This comprehensive guide outlines best practices for designing rigorous and convincing technical evaluations for networked systems. It structures the process by requiring experiments to answer specific questions, advising authors to climb the evidence ladder from synthetic benchmarks to real-world deployment. Key concepts include reporting tail latencies (p99), establishing strong baselines, and maintaining meticulous provenance records to ensure reproducibility.

A comprehensive guide for drafting a structured, double-blind academic rebuttal for conferences (like PerCom). This skill focuses on addressing explicit reviewer questions using only evidence already present in the submitted paper, thereby avoiding the promise of new experiments. It covers maintaining anonymity, structuring arguments, and focusing on core technical dimensions like cross-subject evaluation and metric soundness.

Provides comprehensive guidelines for authors responding to reviewer objections after a major technical conference submission (e.g., PLDI). It details how to triage structural critiques—including factual errors, soundness doubts, and evaluation gaps—and emphasizes maintaining academic rigor, adhering strictly to the original scope, and avoiding promises of unproven new contributions.

A comprehensive guide for structuring the Related Work section for top-tier recommender systems conferences (RecSys). It advises authors on auditing novelty by positioning their contribution against adjacent research fields (e.g., SIGIR, KDD, WSDM), addressing critical lines (like reproducibility and off-policy evaluation), and ensuring the work is technically distinct from prior or concurrent studies.

A comprehensive guide for writing the evaluation section of a systems paper for top-tier conferences. It teaches authors how to map every technical claim to verifiable experiments, establish fair state-of-the-art baselines, utilize mixed workloads (microbenchmarks, E2E applications, and traces), and honestly report critical metrics like performance tails, variance, and overheads. The goal is to maximize credibility and withstand rigorous peer review.

Provides comprehensive guidelines for designing rigorous technical evaluations for interactive systems, specifically tailored for top-tier venues like UIST. It emphasizes matching evaluation methods to specific artifact claims, reporting distributions over means, closing the interaction loop, and performing thorough ablations against real-world baselines. This framework ensures the scientific rigor and credibility of submitted research.

This guide provides a rigorous methodology for achieving scientific reproducibility in technical and user experience papers (e.g., UIST). It details three essential 'ledgers': the Build Ledger (pinning software, hardware, and environment dependencies), the Measurement Ledger (defining precise protocols for metrics like latency and accuracy), and the Study Ledger (documenting human evaluation tasks). Following these protocols ensures that external researchers can accurately rebuild the artifact and validate reported results.