Skill UI

Provides comprehensive guidelines for packaging supplementary materials, including code, data, model weights, and benchmarks, for major machine learning conferences like ICML. It details the requirements for both the double-blind review stage (focusing on anonymization and minimal replication commands) and the final public release package (ensuring permanent public links and clear licensing).

This guide outlines best practices for packaging research artifacts (code, data, proofs, models) submitted for major AI conferences like IJCAI. It helps researchers create convincing, anonymous, and reproducible evidence to support their claims, even when formal artifact evaluation tracks are unavailable.

A comprehensive guide detailing the high standards required for presenting security evidence at major conferences. It covers methodologies for proving claims—including attacks, defenses, and detection systems—across live internet measurements, controlled testbeds, and emulation. Key requirements include adaptive adversary modeling, rigorous measurement hygiene, and adherence to ethical review protocols to ensure results are reproducible and relevant to real-world networks.

A crucial guide for authors preparing for PODC (Proofs venue). It corrects the common misconception that runnable artifacts or badges are required. Instead, it redirects focus to the three core areas of evaluation: ensuring proof completeness, establishing model rigor by declaring all assumptions, and maintaining transparency for optional simulations.

This resource models the complex, multi-stage review process for top-tier academic conferences, such as SOSP. It details the journey of a paper from initial submission through staged reviews, author rebuttal, and the final live committee decision. It helps users understand the structural dynamics of scholarly evaluation and how to strategically respond to reviewers' critiques.

A comprehensive guide detailing the complex submission and evaluation pipeline for TACAS (Tools and Algorithms for Scientific Applications). It models key features such as category-specific blind review, the mandatory parallel artifact evaluation for tool papers, and the single-round conference decision-making process, helping authors strategically prepare their submissions.

A comprehensive guide detailing the rigorous, journal-style review process for IEEE VIS full-paper submissions. It explains the two-phase evaluation structure, the significance of a 'Conditional Accept' (treating it like a major R&R), and how the process differs fundamentally from single-decision conference models (e.g., CVPR, CHI). Essential reading for authors navigating academic publication.