COLT Supplementary Structurer
Structures and optimizes COLT paper appendices and single-PDF body splits for seamless referee verification.
COLT Supplementary is a specialized skill designed for theoretical machine learning researchers preparing submissions for the Conference on Learning Theory (COLT). It guides the delicate balance between the 12-page main body limit and the unlimited-length proof appendix inside a single PDF. By enforcing LaTeX theorem restatement discipline via thm-restate, standardizing notation tables, organizing lemma dependencies, and generating proof roadmaps, this skill helps authors maximize reviewer clarity and minimize cognitive verification overhead.
Key Features
01Implements robust LaTeX theorem restatements using thmtools to prevent drift
02Evaluates 12-page main body versus unlimited appendix content distribution
03Structures proof roadmaps to guide referee verification through complex bounds
04Designs self-contained appendix architectures with symbol tables and auxiliary lemmas
05Identifies common formatting defects like forward-referenced lemmas and unstable page citations
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Use Cases
01Formatting theoretical machine learning proofs for COLT conference submissions
02Refactoring dense mathematical papers to meet strict 12-page main body limits
03Reorganizing sprawling multi-theorem appendices into self-contained, verifiable modules