{"slug": "r-3-advertisement-compliance-rectification-via-group-relative-experience-and", "title": "R^3: Advertisement Compliance Rectification via Group-Relative Experience Extractor and Curriculum Reinforcement", "summary": "Researchers propose R^3, a framework for rectifying textual violations in video advertisements while preserving original semantic intent. The system uses a group-relative compliance experience extractor and curriculum reinforcement learning to balance compliance with intent preservation. Experiments show it outperforms existing methods in industrial settings.", "body_md": "arXiv:2607.07318v1 Announce Type: new\nAbstract: Rigorous content moderation is crucial for online advertising but leads to millions of daily rejections. This scale renders manual rectification infeasible, particularly for video advertisements. However, existing safety-driven methods often suffer from aggressive over-editing, which compromises the advertiser's original semantic intent merely to satisfy compliance. In this work, we target the rectification of textual violations in video ads, covering both speech transcripts and on-screen text. We propose R^3, a novel framework designed to harmonize compliance with original semantic intent preservation. Our approach integrates three key innovations: (1) an experience-driven data synthesis framework that bootstraps high-quality supervision via a group-Relative compliance experience extractor; (2) a curriculum Reinforcement learning strategy with hierarchical rewards designed to enforce compliance while maximizing semantic consistency; and (3) a comprehensive video Rectification framework seamlessly integrating text recognition, rewriting, and re-rendering for industrial deployment. Extensive experiments on industrial datasets and online A/B testing demonstrate that R^3 significantly outperforms state-of-the-art baselines, achieving an optimal trade-off between violation rectification and intent preservation.", "url": "https://wpnews.pro/news/r-3-advertisement-compliance-rectification-via-group-relative-experience-and", "canonical_source": "https://arxiv.org/abs/2607.07318", "published_at": "2026-07-09 04:00:00+00:00", "updated_at": "2026-07-09 04:15:51.193694+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "natural-language-processing", "ai-products"], "entities": [], "alternates": {"html": "https://wpnews.pro/news/r-3-advertisement-compliance-rectification-via-group-relative-experience-and", "markdown": "https://wpnews.pro/news/r-3-advertisement-compliance-rectification-via-group-relative-experience-and.md", "text": "https://wpnews.pro/news/r-3-advertisement-compliance-rectification-via-group-relative-experience-and.txt", "jsonld": "https://wpnews.pro/news/r-3-advertisement-compliance-rectification-via-group-relative-experience-and.jsonld"}}