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cs.CV2026
Visual Token Compression Enhances Robustness of MLLMs
Shishen Gu, Jiequan Cui, Wenbo Hu +3
In this paper, we show for the first time that visual token pruning enhances the robustness of Multimodal Large Language Models (MLLMs), mitigating vulnerabilities such as jailbrea…
cs.CV2026
Layer Consistency Matters: Elegant Latent Transition Discrepancy for Generalizable Synthetic Image Detection
Yawen Yang, Feng Li, Shuqi Kong +4
Recent rapid advancement of generative models has significantly improved the fidelity and accessibility of AI-generated synthetic images. While enabling various innovative applicat…