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Multimodal large language models (MLLMs) remain vulnerable to transferable adversarial examples.
Optimal transport: old and new , volume 338
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Sinkhorn distances: Lightspeed computation of optimal transport
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Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Explaining and harnessing adversarial examples
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AdverTorch v0.1: An adversarial robustness toolbox based on pytorch
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Learning transferable visual models from natural language supervision
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Multimodal few-shot learning with frozen language models
Maria Tsimpoukelli, Jacob L Menick, Serkan Cabi, SM Eslami, Oriol Vinyals, and Felix Hill · 2021
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al · 2022
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Improving the transferability of targeted adversarial examples through object-based diverse input
Junyoung Byun, Seungju Cho, Myung-Joon Kwon, Hee-Seon Kim, and Changick Kim · 2022
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Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned
Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez, Nicholas Schiefer, Kamal Ndousse, et al · 2022
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Frequency domain model augmentation for adversarial attack
Yuyang Long, Qilong Zhang, Boheng Zeng, Lianli Gao, Xianglong Liu, Jian Zhang, and Jingkuan Song · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Red teaming language models with language models
Ethan Perez, Saffron Huang, Francis Song, Trevor Cai, Roman Ring, John Aslanides, Amelia Glaese, Nat McAleese, and Geoffrey Irving · 2022
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Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, et al · 2022
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An empirical study of gpt-3 for few-shot knowledge-based vqa
Zhengyuan Yang, Zhe Gan, Jianfeng Wang, Xiaowei Hu, Yumao Lu, Zicheng Liu, and Lijuan Wang · 2022
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Pandagpt: One model to instruction-follow them all
Yixuan Su, Tian Lan, Huayang Li, Jialu Xu, Yan Wang, and Deng Cai · 2023
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How many unicorns are in this image? a safety evaluation benchmark for vision llms
Haoqin Tu, Chenhang Cui, Zijun Wang, Yiyang Zhou, Bingchen Zhao, Junlin Han, Wangchunshu Zhou, Huaxiu Yao, and Cihang Xie · 2023
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Instructta: Instruction-tuned targeted attack for large vision-language models
Xunguang Wang, Zhenlan Ji, Pingchuan Ma, Zongjie Li, and Shuai Wang · 2023
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Black-box sparse adversarial attack via multi-objective optimisation
Phoenix Neale Williams and Ke Li · 2023
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Visual chatgpt: Talking, drawing and editing with visual foundation models
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al · 2023
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Image hijacks: Adversarial images can control generative models at runtime
Luke Bailey, Euan Ong, Stuart Russell, and Scott Emmons · 2023
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Are aligned neural networks adversarially aligned?
Nicholas Carlini, Milad Nasr, Christopher A Choquette-Choo, Matthew Jagielski, Irena Gao, Anas Awadalla, Pang Wei Koh, Daphne Ippolito, Katherine Lee, Florian Tramer, et al · 2023
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Rethinking model ensemble in transfer-based adversarial attacks
Huanran Chen, Yichi Zhang, Yinpeng Dong, Xiao Yang, Hang Su, and Jun Zhu · 2023
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Palm: Scaling language modeling with pathways
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How robust is google’s bard to adversarial image attacks?
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Llama-adapter v2: Parameter-efficient visual instruction model
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On evaluating adversarial robustness of large vision-language models
Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, and Min Lin · 2023
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A survey on multimodal large language models for autonomous driving
Can Cui, Yunsheng Ma, Xu Cao, Wenqian Ye, Yang Zhou, Kaizhao Liang, Jintai Chen, Juanwu Lu, Zichong Yang, Kuei-Da Liao, et al · 2024
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Sensen Gao, Xiaojun Jia, Xuhong Ren, Ivor Tsang, and Qing Guo · 2024
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Agent smith: A single image can jailbreak one million multimodal llm agents exponentially fast
Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Ye Wang, Jing Jiang, and Min Lin · 2024
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Efficient generation of targeted and transferable adversarial examples for vision-language models via diffusion models
Qi Guo, Shanmin Pang, Xiaojun Jia, Yang Liu, and Qing Guo · 2024
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Questioning, answering, and captioning for zero-shot detailed image caption
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Vision-r1: Incentivizing reasoning capability in multimodal large language models
Wenxuan Huang, Bohan Jia, Zijie Zhai, Shaosheng Cao, Zheyu Ye, Fei Zhao, Zhe Xu, Yao Hu, and Shaohui Lin · 2025
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Natural language understanding and inference with mllm in visual question answering: A survey
Jiayi Kuang, Ying Shen, Jingyou Xie, Haohao Luo, Zhe Xu, Ronghao Li, Yinghui Li, Xianfeng Cheng, Xika Lin, and Yu Han · 2025
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Zhaoyi Li, Xiaohan Zhao, Dong-Dong Wu, Jiacheng Cui, and Zhiqiang Shen · 2025
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Image captioning evaluation in the age of multimodal llms: Challenges and future perspectives
Sara Sarto, Marcella Cornia, and Rita Cucchiara · 2025
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