R^3

R^3: Curriculum reinforcement learning framework for automated ad compliance rectification in video

Researchers propose R^3, a framework for automatically rectifying textual violations in video advertisements (speech transcripts and on-screen text) while preserving advertiser semantic intent. The system combines a group-relative compliance experience extractor for data synthesis, a curriculum reinforcement learning strategy with hierarchical rewards, and an end-to-end video rectification pipeline covering text recognition, rewriting, and re-rendering. Experiments on industrial datasets and A/B testing show R^3 outperforms baselines on the compliance-vs-intent trade-off.