3 accepted papers
Multimodal large reasoning models (MLRMs) are increasingly deployed for vision-language tasks that produce explicit intermediate rationales. However, reasoning traces can contain unsafe content even when the final answer is non-harmful, creating deployment risks. Existing multimodal safety guards pr
Recently, vulnerable samples have been shown to be crucial for improving adversarial training performance. Our analysis on existing vulnerable samples mining methods indicate that existing methods have two problems: 1) valuable connections among different pairs of natural samples and their adversari…
"Intra-frame inconsistency has been proved to be effective for the generalization of face forgery detection. However, learning to focus on these inconsistency requires extra pixel-level forged location annotations. Acquiring such annotations is non-trivial. Some existing methods generate large-scale…