AI RESEARCH
QwenSafe: Multimodal Content Rating Description Identification via Preference-Aligned VLMs
arXiv CS.CV
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ArXi:2605.20584v1 Announce Type: new Mobile app marketplaces require developers to disclose standardized content rating descriptors (CRDs) to inform users about potentially sensitive or restricted content. Ensuring the accuracy and consistency of these disclosures remains challenging due to the multimodal nature of app content, which spans textual descriptions and visual interfaces. In this paper, we present QwenSafe, a Vision-Language Model (VLM) designed to automatically identify the presence of Apple-defined CRDs by jointly reasoning over app metadata and screenshots. To enable scalable.