AutoCut: End-to-end advertisement video editing based on multimodal discretization and controllable generation

ArXi:2603.28366v1 Announce Type: new Short-form videos have become a primary medium for digital advertising, requiring scalable and efficient content creation. However, current workflows and AI tools remain disjoint and modality-specific, leading to high production costs and low overall efficiency. To address this issue, we propose AutoCut, an end-to-end advertisement video editing framework based on multimodal discretization and controllable editing.