COLT Paper Submission Auditor
Audits machine learning theory papers for COLT conference submission compliance, PMLR formatting, anonymity, and CMT readiness.
The COLT Paper Submission Auditor streamlines preparation for the Conference on Learning Theory (COLT) by validating manuscripts against strict PMLR guidelines and venue-specific requirements. It audits the 12-page main body limit, ensures single-PDF compilation with unlimited appendix, checks double-anonymous compliance, and verifies parallel-submission rules across journals and proceedings. Ideal for ML theorists and researchers aiming to eliminate desk-reject risks before the AoE deadline, this skill automates the critical pre-submission checklist.
Características Principales
01Validates double-anonymous review compliance across text, metadata, and repository links
02Audits manuscript layout against 12-page PMLR main body limits and single-PDF requirements
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04Evaluates parallel-submission policies across journals, proceedings, and arXiv preprints
05Provides a prioritized final-week checklist to prevent statement-proof drift and late errors
06Assists with Microsoft CMT portal configurations, subject area selection, and conflict management
Casos de Uso
01Formatting verification for PMLR-style LaTeX documents including body and appendix boundary inspection
02Pre-submission compliance checks for learning theory papers submitted to COLT
03Double-anonymous sweeps across manuscript text, acknowledgements, citations, and PDF metadata