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Different from traditional task-specific vision models, recent large VLMs can readily adapt to different vision tasks by simply using different textual instructions, i.e., prompts.
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Towards efficient adversarial training on vision transformers
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Auto-encoding scene graphs for image captioning
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Fooled by imagination: Adversarial attack to image captioning via perturbation in complex domain
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Controlled caption generation for images through adversarial attacks
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Adversarial vqa: A new benchmark for evaluating the robustness of vqa models
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Learning transferable adversarial perturbations
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Openflamingo: An open-source framework for training large autoregressive vision-language models
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Instructblip: Towards general-purpose vision-language models with instruction tuning
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Universal and transferable adversarial attacks on aligned language models
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