Skill UI

A comprehensive guide for computer vision researchers on strategically positioning their work. It helps assess whether the core contribution is related to visual data or visual computation, providing fit tests and a routing map to recommend the most appropriate top-tier conferences (CVPR, ICCV, NeurIPS) or journals based on the contribution type and technical maturity.

A comprehensive guide for computer vision researchers to determine if their project is a good fit for ECCV, considering scope, technical durability, and academic timing. It weighs the project's contribution against the specific requirements of ECCV versus competing top-tier venues like CVPR and ICCV, ensuring strategic submission planning.

A comprehensive guide for authors submitting their final, camera-ready version of an accepted EMNLP paper. It details the critical, multi-stage process, including merging reviewed edits, restoring author identity and public links, verifying Anthology metadata, and publishing associated artifacts. This ensures the manuscript meets all strict academic publishing and technical standards.

This comprehensive guide helps authors navigate the complex decision of where to submit their Human-Robot Interaction (HRI) research. It outlines critical criteria, including the robot-embodiment and human-in-the-loop tests, to determine the correct venue (e.g., HRI, CHI, ICRA/IROS). Furthermore, it details the five specialized tracks within HRI and advises authors on matching their primary technical contribution to the most suitable academic domain.

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.

This guide helps transform technically sound machine learning drafts into highly readable, conference-ready papers suitable for ICLR and OpenReview. It emphasizes structuring the core learning-representation insight upfront, clarifying contribution types (method, theory, benchmark), optimizing for public skimming, and providing clear reviewer navigation paths. Use this when ensuring maximum impact and clarity in a challenging academic review environment.

This guide provides structured methodologies for authors to position their research within the context of existing literature and concurrent submissions at top-tier machine learning conferences (e.g., ICML, NeurIPS). It emphasizes identifying the technical delta, addressing novelty concerns, and properly citing related work to maximize acceptance chances.

This guide offers detailed guidelines for assembling and auditing supplementary materials for top-tier AI conferences (e.g., IJCAI). It covers critical aspects like separating the technical appendix from resubmission files, ensuring anonymity across all artifacts, maintaining the self-contained nature of the core paper, and managing source code and data for maximum reproducibility.

A comprehensive framework for researchers to assess if their AI research contribution is best suited for a major conference like IJCAI, or if a highly specialized venue (such as NeurIPS, ICML, CVPR, or ACL) would provide a clearer audience. It guides decisions based on technical depth, problem scope, and contribution type.

A comprehensive guide for authors targeting the International Conference on Autonomous Agents and Multiagent Systems (AAMAS). This skill helps authors strategically position their work by focusing on core themes like autonomous agents, multiagent learning, game-theoretic interaction, and decentralized decision-making. It covers submission framing, evidence requirements, and risk assessment to ensure manuscripts align with the venue's technical focus.

This comprehensive guide outlines the strict technical and structural requirements for the IROS supplementary video, which serves as primary evidence for submitted research. It details constraints such as the 60-second limit, 10MB size cap, and necessary formats. The guide emphasizes presenting uncut real trials, including labeled failures, maintaining honest playback speed, and performing thorough anonymization to maximize academic credibility.

Provides a comprehensive, detailed audit checklist for authors submitting papers intended for NAACL. This guide walks through the complex ACL Rolling Review (ARR) submission cycle, ensuring the manuscript passes all mandatory technical gates—such as anonymity checks, format compliance, structural requirements, and accurate declaration—before the final conference commitment. Essential for navigating the unique timeline and rigorous standards of top NLP conferences.