# Counterfactual Neighborhood Risk Fields: Evidence-Grounded Selective Safety for Vision-Language Models

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**Published:** 16 октября 2026 г.
**Author:** Tianshi Wang, Jingsong Wang, Fengling Li, Jingjing Li, Xin Li, Lei Zhu
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/ru/articles/counterfactual-neighborhood-risk-fields-evidence-grounded-selective-safe

arXiv:2610.20679v1 Announce Type: new Abstract: Representation-based safety defenses for vision-language models (VLMs) often learn to separate harmful from benign inputs, but separation alone does not establish what a risk score means or when it should be trusted. We introduce…

> Материал агрегирован из первоисточника: **arXiv — cs.AI**
> [Читать полностью в arXiv — cs.AI](https://arxiv.org/abs/2610.20679)

**Теги:** #arXiv

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