Skill UI

This guide details the process of packaging artifacts for academic conferences (ICLR), ensuring that research claims are fully reproducible and reviewable. It emphasizes providing minimal reproduction paths, maintaining data provenance, rigorously anonymizing metadata to protect authors' identities, and creating robust, permanent records for the scholarly community.

A comprehensive self-auditing guide designed for authors preparing manuscripts for submission to top-tier academic journals. It systematically addresses recurring, structural, and critical flaws across theory contribution, econometric identification, mechanism explanation, heterogeneity analysis, and writing conventions. This tool helps authors proactively identify and correct potential weaknesses before facing peer review.

Provides a comprehensive guide for preparing an accepted academic paper for camera-ready submission, detailing the necessary steps after acceptance. This workflow covers de-anonymization, integrating reviewer feedback, writing lay summaries, running format checks, and managing public-facing records such as reviews and conflict disclosures, ensuring publication readiness for top-tier conferences.

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.

A comprehensive guide detailing the academic standards for ensuring research reproducibility at ICSE. Covers open-science policies, mandatory data availability statements, techniques for pinning provenance (especially for mining and LLMs), and best practices for maintaining verifiability while ensuring anonymity. Essential for academic submissions.

A comprehensive guide for researchers submitting academic papers to ensure high standards of reproducibility and verifiable evidence. It covers critical areas such as data-availability statements, artifact management, provenance pinning (for LLMs and mining), and mapping claims directly to evidence, adhering to rigorous academic standards.

A comprehensive guide modeling the specific, single-round, double-anonymous review pipeline for IEEE ICSME submissions. It details the crucial early-decision cut (Accept, Reject, Response Recommended) and emphasizes that unlike journal submissions, there are no Major Revision rounds. Use this to strategically plan your research submission and response artifact.

This skill provides comprehensive guidance for authors seeking to submit manuscripts to the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). It helps evaluate the fit of research in signal processing, speech, audio, and image processing. It guides the framing, required empirical evidence (mathematical models, reproducible validation), and optimal positioning of the paper to maximize acceptance chances.

A comprehensive guide for authors submitting data mining research to elite computer science venues like ICDM. This skill helps define the paper's fit, target the correct scope (algorithms, graph mining, etc.), and structure the manuscript to meet rigorous academic standards. It emphasizes providing sufficient evidence, rigorous baselines, and clear positioning relative to the conference's focus.

A comprehensive guide for positioning visualization and visual analytics manuscripts for the IEEE Pacific Visualization Symposium (PacificVis). This skill helps authors refine their scope, evidence presentation, and overall narrative to match the unique requirements and review expectations of this top-tier conference. It acts as a fit/framing tool for conference submission strategy, ensuring the work is appropriately targeted for the Asia-Pacific community focus.

A comprehensive guide for authors submitting manuscripts to IEEE Transactions on Medical Imaging (TMI). It details the journal's specific scope, required technical rigor, necessary validation standards, and structure, emphasizing that contributions must be medical-imaging-specific rather than generic computer vision methods. This tool helps authors assess fit, re-frame their work, and anticipate submission requirements.

This guide provides comprehensive strategic advice for authors targeting the IEEE Visualization Conference (IEEE VIS). It covers conference positioning, scope fitting, required evidence (visual encoding, evaluation), and helps authors re-frame their work from journal or arXiv formats into a selective, high-impact conference narrative. Use it when determining if a research manuscript is appropriate for IEEE VIS.