Counterfactual neighborhood risk fields: evidence-grounded selective safety for vision-language models
Read original on arXiv cs.AI ↗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...
Original headline: "Counterfactual Neighborhood Risk Fields: Evidence-Grounded Selective Safety for Vision-Language Models"
Timeline
- October 17, 2026 Counterfactual Neighborhood Risk Fields: Evidence-Grounded Selective Safety for Vision-Language Models arXiv cs.AI