Skill UI

This guide outlines the complete project management workflow for major computer vision conferences like ECCV, CVPR, and ICCV. It covers the entire academic cycle, from initial registration and submission through peer review, acceptance, camera-readiness, and post-conference retargeting strategies. Useful for research teams planning multiple submissions across even and odd years.

A comprehensive project management guide for submitting interdisciplinary, responsible AI papers to major academic conferences like FAccT. It provides a detailed backward-planning timeline, covering milestones from initial abstract registration and literature review to revisions, camera-ready submission, and conference presentation, emphasizing ethical considerations and structured academic processes.

A comprehensive guide detailing the critical workflow from paper acceptance to final camera-ready submission for major computational conferences (like ICCV). It covers technical requirements such as de-anonymization, synchronizing multiple public copies (arXiv, CVF, IEEE), updating URLs, and managing logistical details for presentation.

A comprehensive guide for authors preparing the 'Related Work' section for top-tier robotics conferences like ICRA. It details how to conduct thorough literature reviews across multiple research 'lanes,' handle concurrent work (arXiv), properly self-cite under double-anonymous rules, and position the novelty against both academic rivals and commercial systems.

This skill is a strategic guide for authors submitting to top-tier AI conferences, specifically the International Conference on Principles of Knowledge Representation and Reasoning (KR). It helps users assess manuscript fit, framing, and evidence requirements. It provides deep guidance on the required scope, such as formal semantics, nonmonotonic reasoning, and ontologies, ensuring the paper is positioned correctly within the specialized KR community. Ideal for pre-submission strategy and manuscript re-framing.

A comprehensive guide for authors preparing rebuttals to multiple reviewers at INTERSPEECH. It provides strategic advice on tailoring responses to diverse expert profiles (e.g., speech engineers vs. scientists), managing the 4-page constraint, maintaining anonymity, and structuring responses to maximize impact on the meta-reviewer. Essential for authors navigating the competitive academic publication process.

A comprehensive guide for writing the 'Related Work' section for top-tier speech conference papers. It teaches authors how to trace the academic lineage of a task across multiple venues (e.g., ISCA, ICASSP, NeurIPS), properly cite canonical corpora and metrics, and condense complex literature reviews into concise, contrastive clauses.

This comprehensive guide instructs researchers on how to design rigorous and credible evaluations for Machine Learning systems. It covers critical areas such as workload selection, baseline comparison discipline, reporting four key coordinates (throughput, latency tails, memory, cost), structuring ablations, and generating scaling evidence. It ensures measurements meet academic benchmarking standards.

A comprehensive guide for authors targeting Nature Machine Intelligence. It outlines the high standard required for AI/ML research, emphasizing conceptual significance, real-world impact, interdisciplinary relevance, and rigorous ethical and methodological depth. Use this tool to assess fit and framework your submission for a Nature-family audience.

This skill provides a comprehensive framework for authors targeting top-tier AI conferences like NeurIPS. It guides researchers in refining their manuscript's narrative, ensuring the contribution meets the venue's standards for broad, high-novelty machine learning research. It covers topic fit, evidence bar requirements, structuring the argument, handling interdisciplinary claims, and navigating the specific submission cycle rules for maximizing acceptance chances.

This skill guides authors on positioning foundational and conceptually general robotics research for submission to The International Journal of Robotics Research (IJRR). It evaluates the manuscript's depth, generality, and conceptual framework, helping authors re-frame single-demonstration results into field-advancing principles. It also assists in choosing between IJRR and competing venues like IEEE Transactions on Robotics (T-RO).

A comprehensive guide for structuring the 'Related Work' section in academic papers, especially in Computer Vision (CV). It teaches authors how to strategically position their research contribution by covering multiple literature shelves: vision methods, domain constraints, concurrent arXiv work, and prior art. This ensures the paper clearly defines a unique gap rather than merely listing citations, adhering to double-blind review standards.