**SafeAtlas-VL: Beyond Binary Multimodal Safety with Large-Scale Data and Guard Models**

> Multimodal safety moderation requires distinguishing risks arising from visual content, user intent, and assistant behavior. Existing safeguards, however, are typically trained for a single judgment target and reduce safety assessment to a binary decision. Consequently, risk becomes difficult to compare across a multimodal interaction, and ambiguous cases are obscured. We introduce SafeAtlas-VL, a dataset of 1.5M tra...

**来源信息**
- **来源**:HuggingFace Daily Papers(社区热门论文)
- **分类**:论文
- **发布时间**:2026-09-01 08:00(北京时间)
- **原文**:[打开原文](https://huggingface.co/papers/2608.29098)