Skill UI

A comprehensive guide detailing the empirical writing style required for EMNLP submissions. It emphasizes scoping claims to specific datasets and languages, ensuring examples are load-bearing, structuring the argument phenomenon-first, and accurately calibrating hedging language based on evidence strength.

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.

Provides comprehensive guidelines for authors submitting to major AI conferences. It helps authors audit originality, properly cite prior art (including preprints, workshop papers, and rejected versions), manage dual-submission risks, and transform the related work section from a mere list into a compelling, novel argument that clearly positions the contribution.

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.

A comprehensive guide detailing the highly structured, multi-stage peer review process used by top-tier robotics conferences (such as RSS). It covers the mechanics from double-blind submission and threshold gating to the role of the Area Chair. Learn how to structure your arguments, write compelling rebuttals, and summarize findings to maximize acceptance chances in highly selective academic venues.