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cs.CV2026
Sparse Autoencoders as Plug-and-Play Firewalls for Adversarial Attack Detection in VLMs
Hao Wang, Yiqun Sun, Pengfei Wei +2
Vision-language models (VLMs) have advanced rapidly and are increasingly deployed in real-world applications, especially with the rise of agent-based systems. However, their safety…
cs.CV2026
Jagle: Building a Large-Scale Japanese Multimodal Post-Training Dataset for Vision-Language Models
Issa Sugiura, Keito Sasagawa, Keisuke Nakao +8
Developing vision-language models (VLMs) that generalize across diverse tasks requires large-scale training datasets with diverse content. In English, such datasets are typically c…