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Large vision-language models (VLMs) such as GPT-4 have achieved unprecedented performance in response generation, especially with visual inputs, enabling more creative and adaptable interaction than large language models such as ChatGPT.
Imagenet: A large-scale hierarchical image database
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Evasion attacks against machine learning at test time
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Microsoft coco: Common objects in context
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Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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Delving into transferable adversarial examples and black-box attacks
Yanpei Liu, Xinyun Chen, Chang Liu, and Dawn Song · 2016
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Transferability in machine learning: from phenomena to black-box attacks using adversarial samples
Nicolas Papernot, Patrick McDaniel, and Ian Goodfellow · 2016
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Grad-cam: Visual explanations from deep networks via gradient-based localization
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Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang · 2018
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Practical black-box attacks on deep neural networks using efficient query mechanisms
Arjun Nitin Bhagoji, Warren He, Bo Li, and Dawn Song · 2018
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Grad-cam++: Generalized gradient-based visual explanations for deep convolutional networks
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Yinpeng Dong, Fangzhou Liao, Tianyu Pang, Hang Su, Jun Zhu, Xiaolin Hu, and Jianguo Li · 2018
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Black-box adversarial attacks with limited queries and information
Andrew Ilyas, Logan Engstrom, Anish Athalye, and Jessy Lin · 2018
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2018
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Attacks meet interpretability: Attribute-steered detection of adversarial samples
Guanhong Tao, Shiqing Ma, Yingqi Liu, and Xiangyu Zhang · 2018
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Improving black-box adversarial attacks with a transfer-based prior
Shuyu Cheng, Yinpeng Dong, Tianyu Pang, Hang Su, and Jun Zhu · 2019
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Evading defenses to transferable adversarial examples by translation-invariant attacks
Yinpeng Dong, Tianyu Pang, Hang Su, and Jun Zhu · 2019
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Adversarial examples are not bugs, they are features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Anish Athalye, Tran, and Aleksander Madry · 2019
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Quantifying the carbon emissions of machine learning
Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, and Thomas Dandres · 2019
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Language models are unsupervised multitask learners
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Trick me if you can: Human-in-the-loop generation of adversarial examples for question answering
Eric Wallace, Pedro Rodriguez, Shi Feng, Ikuya Yamada, and Jordan Boyd-Graber · 2019
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Improving transferability of adversarial examples with input diversity
Cihang Xie, Zhishuai Zhang, Yuyin Zhou, Song Bai, Jianyu Wang, Zhou Ren, and Alan L Yuille · 2019
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Exact adversarial attack to image captioning via structured output learning with latent variables
Yan Xu, Baoyuan Wu, Fumin Shen, Yanbo Fan, Yong Zhang, Heng Tao Shen, and Wei Liu · 2019
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Generating fluent adversarial examples for natural languages
Huangzhao Zhang, Hao Zhou, Ning Miao, and Lei Li · 2019
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Language models are few-shot learners
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Is bert really robust? a strong baseline for natural language attack on text classification and entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits · 2020
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A geometry-inspired attack for generating natural language adversarial examples
Zhao Meng and Roger Wattenhofer · 2020
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Reevaluating adversarial examples in natural language
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Adversarial nli: A new benchmark for natural language understanding
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Generating natural language adversarial examples on a large scale with generative models
Yankun Ren, Jianbin Lin, Siliang Tang, Jun Zhou, Shuang Yang, Yuan Qi, and Xiang Ren · 2020
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On the transferability of adversarial attacksagainst neural text classifier
Liping Yuan, Xiaoqing Zheng, Yi Zhou, Cho-Jui Hsieh, and Kai-Wei Chang · 2020
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Controlled caption generation for images through adversarial attacks
Towards the detection of diffusion model deepfakes
Jonas Ricker, Simon Damm, Thorsten Holz, and Asja Fischer · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 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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De-fake: Detection and attribution of fake images generated by text-to-image diffusion models
Zeyang Sha, Zheng Li, Ning Yu, and Yang Zhang · 2022
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Promptattack: Prompt-based attack for language models via gradient search
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Nayyer Aafaq, Naveed Akhtar, Wei Liu, Mubarak Shah, and Ajmal Mian · 2021
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Improving question answering model robustness with synthetic adversarial data generation
Max Bartolo, Tristan Thrush, Robin Jia, Sebastian Riedel, Pontus Stenetorp, and Douwe Kiela · 2021
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Query-efficient black-box adversarial attacks guided by a transfer-based prior
Yinpeng Dong, Shuyu Cheng, Tianyu Pang, Hang Su, and Jun Zhu · 2021
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Divyansh Kaushik, Douwe Kiela, Zachary C Lipton, and Wen-tau Yih · 2021
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Generating natural language attacks in a hard label black box setting
Rishabh Maheshwary, Saket Maheshwary, and Vikram Pudi · 2021
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Evaluating the robustness of neural language models to input perturbations
Milad Moradi and Matthias Samwald · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Yundi Shi, Piji Li, Changchun Yin, Zhaoyang Han, Lu Zhou, and Zhe Liu · 2022
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Shaden Smith, Mostofa Patwary, Brandon Norick, Patrick LeGresley, Samyam Rajbhandari, Jared Casper, Zhun Liu, Shrimai Prabhumoye, George Zerveas, Vijay Korthikanti, et al · 2022
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Plug-and-play vqa: Zero-shot vqa by conjoining large pretrained models with zero training
Anthony Meng Huat Tiong, Junnan Li, Boyang Li, Silvio Savarese, and Steven CH Hoi · 2022
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Versatile diffusion: Text, images and variations all in one diffusion model
Xingqian Xu, Zhangyang Wang, Eric Zhang, Kai Wang, and Humphrey Shi · 2022
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Boosting transferability of targeted adversarial examples via hierarchical generative networks
Xiao Yang, Yinpeng Dong, Tianyu Pang, Hang Su, and Jun Zhu · 2022
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https://twitter.com/sama/status/1635687855921172480
Sam Altman, 2023 · 2023
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, 2023
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How robust is google’s bard to adversarial image attacks?
Yinpeng Dong, Huanran Chen, Jiawei Chen, Zhengwei Fang, Xiao Yang, Yichi Zhang, Yu Tian, Hang Su, and Jun Zhu · 2023
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Palm-e: An embodied multimodal language model
Danny Driess, Fei Xia, Mehdi SM Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, et al · 2023
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Copilot x, 2023
GitHub · 2023
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Language is not all you need: Aligning perception with language models
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Llama: Open and efficient foundation language models
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