Skill UI

Provides a comprehensive, time-sensitive playbook for authors responding to reviews (rebuttals) at MLSys. It details how to triage objections, prioritize critical missing measurements, address systems objections regarding workload representativeness and baseline tuning, and structure anonymous, data-driven replies within a compressed rebuttal window.

This guide details the critical steps for authors preparing their accepted paper for final publication in MLSys proceedings. It covers de-anonymization, restoring company and repository identity, reconciling promised rebuttals, and ensuring metadata accuracy for long-term findability. Essential for managing the complex post-acceptance timeline.

This guide provides critical structuring advice for authors submitting ML Systems papers, focusing on the strategic division of content between the mandatory 10-page body and the unlimited supplementary appendix. It outlines which material belongs in the main text (claims that must be believed) versus what belongs in the appendix (material that must be verifiable evidence, such as full hyperparameter grids or deep ablations).