2 papers
cs.LG2026
VLMGuard: Bootstrapping Malicious Prompt Detectors from Unlabeled Vision-Language Prompts in the Wild
Junlin Fang, Wenyu Chen, Reshmi Ghosh +7
Vision-language Models (VLMs) are essential for contextual understanding of both visual and textual information. However, their vulnerability to adversarially manipulated inputs pr…
cs.CV2026
Mitigating Hallucinations in Large Vision-Language Models via Causal Route Gating
Zhe Cheng, Wenyu Chen, Fode Zhang +1
Large vision-language models (LVLMs) often hallucinate content that is fluent yet unsupported by the image, limiting their reliability in real-world deployment. We show that a key…