Skill UI

A comprehensive framework for ensuring rigorous scientific reproducibility in systems papers. It details how to establish a full provenance ledger (tracking hardware, software commits, and workloads), manage performance variance through repeated runs and statistical reporting, and implement automated pipelines so that all reported figures can be regenerated from raw data.

A comprehensive guide for authors submitting to FAccT, detailing the process of responding to academic reviews. It distinguishes between the short factual rebuttal (Turn 1) and the structured Revise-and-resubmit response (Turn 2). The guide emphasizes maintaining strict anonymity, correcting misreadings, and using a structured 'change ledger' to address every prioritized concern.

A comprehensive guide for authors responding to technical reviews at top-tier conferences. It differentiates between the initial rebuttal and the final change ledger, providing best practices for addressing reviewer concerns regarding measurement soundness, consistency, and performance. Focuses heavily on maintaining double-blind anonymity while strengthening technical arguments.

A comprehensive methodology guide for achieving maximum checkability in theoretical computer science proofs, especially for high-stakes academic venues like FOCS. It outlines five critical practices: maintaining a hypothesis ledger, freezing theorem statements across all document versions, auditing external theorems, providing certificates for computed steps, and handling errata formally. This ensures proofs withstand intense academic scrutiny.

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 structuring author responses to major academic conference reviews (e.g., ICSE). It distinguishes between the initial 'author response' and the structured 'Major Revision' letter. Learn how to address specific review criteria (Novelty, Rigor, Relevance, Verifiability) using a technical, neutral 'ledger' format, ensuring every claim is evidence-based and professionally presented.

Comprehensive guide for converting an accepted academic paper into the final camera-ready version for IEEE proceedings. It details crucial post-acceptance steps, including working through the shepherd's concern ledger, mandatory inclusion of the ethics section, de-anonymizing sensitive technical details (like vendor names and CVEs), and adhering to strict IEEE formatting and submission mechanics. Essential for authors finalizing submissions.

A comprehensive guide for structuring the evidence bundle required for robotics research submissions. It details the critical components—including hardware ledgers, time-stamped logs, configuration files, code, and data—necessary to ensure that scientific claims are fully auditable and reproducible, addressing the needs of skeptical reviewers.

This guide establishes standards for reporting reproducibility in robotics research, addressing the difference between traditional ML and physical systems. It mandates that every claim must be classified as either 'rerunnable' (executable code/simulation) or 'auditable' (detailed logs, hardware specs, and protocols). It covers creating a complete evidence map, detailing the hardware specification ledger, explicitly reporting the sim-to-real gap, and writing an honest availability statement, all within the main paper body.

This guide provides a comprehensive deep dive into the multi-stage peer review process for academic submissions, detailing the roles of EIC, Senior Editor, and Associate Editor. It teaches users how to correctly interpret complex decision letters, distinguish between fundamental contribution gaps and minor execution issues, and structure a preparatory ledger to set realistic expectations for revision rounds.

This guide provides a comprehensive framework for drafting authoritative author responses during academic conference reviews (e.g., ISSTA). It covers triage strategies, distinguishing between factual corrections and promised changes, and structuring a Major-Revision ledger. Learn how to address reviewer concerns strategically, maintain anonymity, and anchor all claims to evidence for maximizing acceptance chances.

A detailed guide for constructing a comprehensive robustness ledger in empirical financial research, particularly for microstructural data. It structures checks to address common academic threats, such as measurement bias, sample selection, microstructure noise (e.g., bid-ask bounce), and flawed inference, ensuring findings are methodologically sound and highly defensible in top-tier journals.