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Robótica & RL
R^3: Advertisement Compliance Rectification via Group-Relative Experience Extractor and Curriculum Reinforcement
arXiv:2607.07318v1 Announce Type: new Abstract: 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, cover...
arXiv cs.CL
·Yuan Chen, Zhenyu Hu, Mengge Xue, Te Cao, Liqun Liu, Peng Shu, Huan Yu, Jie Jiang
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