COLT Paper Writing Style
Refines theoretical machine learning papers for COLT submission with theorem-first exposition, proof overview structuring, and rigorous mathematical hygiene.
The COLT Writing Style skill assists researchers and machine learning theorists in preparing and revising manuscripts for the Conference on Learning Theory (COLT). It guides authors through constructing a referee-efficient first-pages arc, pairing informal and formal theorem statements, enforcing quantifier and parameter hygiene, and budgeting mathematical arguments across the 12-page PMLR limit. Whether polishing proof overviews, auditing abstract formulas, or eliminating mathematical marketing jargon, this skill ensures your theoretical research submission adheres strictly to COLT's peer-review culture and technical standards.