Skill UI

A comprehensive guide for authors submitting academic papers to the ACM Symposium on Virtual Reality Software and Technology (VRST). This resource helps determine conference fit, frame the research contribution, and outlines the specific evidence (software, performance, immersive systems) required to meet the stringent standards of top-tier immersive computing venues.

A comprehensive guide for authors targeting the ACM Workshop on Hot Topics in Networks (HotNets). This skill helps determine conference fit, refine manuscript framing, and assess the evidence required for early-stage networking ideas and provocative systems. It serves as a crucial tool for submission strategy, ensuring the paper is tailored for a selective CS conference audience.

This comprehensive guide details the essential steps required to transition an accepted, anonymous conference paper into the final, public 'camera-ready' version for major academic publications like ACM MM. It covers de-anonymization, completing ACM eRights forms, incorporating CCS concepts, releasing permanent code/data artifacts, and preparing for the final presentation.

A comprehensive checklist for auditing academic submissions to ACM Multimedia (ACM MM). Covers thematic area selection, formatting constraints (6-8 page limit), enforcing double-blind anonymity, managing OpenReview mechanics, and identifying common desk-reject triggers. Essential for authors preparing technical papers for top-tier conferences.

This comprehensive guide outlines the entire end-to-end workflow for submitting and presenting at ACM Multimedia (ACM MM). It breaks down the complex process into distinct phases—from initial thematic scoping and track selection, through the OpenReview abstract submission, paper and supplement delivery, rebuttal, decision, camera-ready preparation, and final conference presentation. It provides actionable advice, risk mitigation strategies, and re-targeting options for both success and rejection.

A comprehensive guide for revising technical papers submitted to ACM Multimedia (ACM MM). It teaches authors how to shift focus from single-modality benchmarks to cross-modal fusion mechanisms, ensuring all media elements (figures, audio, video) function as direct evidence. The guide emphasizes structuring the argument within a tight 6-8 page conference limit, making the multimedia contribution visible from page one.

This guide details the critical steps required after conference acceptance to prepare a paper for the final, public 'camera-ready' submission (e.g., AISTATS, PMLR). It covers transforming an anonymous manuscript into the final two-column format, restoring author metadata, handling public artifacts (code, data), resolving formatting issues, and confirming all presentation and copyright obligations.

A comprehensive guide for academics submitting AI and statistical research papers. It details how to map every claim (theoretical, algorithmic, or empirical) to verifiable evidence, covering necessary details like datasets, hyperparameters, random seeds, compute resources, and uncertainty estimates. It outlines the standards for achieving high levels of reproducibility, from descriptive to turnkey, ensuring scientific rigor for top-tier conferences.

This comprehensive guide provides authors with a detailed audit checklist for preparing submissions for major AI conferences like AISTATS. It covers critical pre-submission requirements, including maintaining double-blind anonymity, adhering to strict page limits, managing OpenReview details, and ensuring reproducibility. Use this checklist before the abstract or full-paper deadline to mitigate desk-reject risks.

This guide provides comprehensive best practices for preparing supplementary materials for major academic conferences like AISTATS. It details the proper structure and handling of appendices, mathematical proofs, code archives, and additional data tables, ensuring that the main paper remains fully understandable even if the supplementary material is ignored by reviewers. Essential for publishing high-quality, robust research.

A comprehensive project management guide for the entire academic lifecycle of submitting a paper to a top-tier conference like AISTATS. It maps all crucial milestones—from initial venue fit and evidence freezing to abstract submission, review discussion, and final camera-ready publication—providing backward-planning heuristics and risk assessment to ensure timely and high-quality submissions.

This guide provides comprehensive rules for authors revising technical papers for top AI/Statistics conferences like AISTATS. It emphasizes achieving statistical rigor, explicitly stating assumptions, pairing every claim with proof or evidence, ensuring conciseness (e.g., adhering to an 8-page limit), and maintaining double-blind academic style. Perfect for PhD students or researchers preparing manuscripts for highly technical review.