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Multimodal contrastive learning aims to train a general-purpose feature extractor, such as CLIP, on vast amounts of raw, unlabeled paired image-text data.
Nus-wide: a real-world web image database from national university of singapore. In
Tat-Seng Chua, Jinhui Tang, Richang Hong, Haojie Li, Zhiping Luo, and Yantao Zheng. 2009 · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton. 2009 · 2009
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Collecting image annotations using amazon’s mechanical turk. In
Cyrus Rashtchian, Peter Young, Micah Hodosh, and Julia Hockenmaier. 2010 · 2010
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A new approach to cross-modal multimedia retrieval. In
Nikhil Rasiwasia, Jose Costa Pereira, Emanuele Coviello, Gabriel Doyle, Gert RG Lanckriet, Roger Levy, and Nuno Vasconcelos. 2010 · 2010
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An analysis of single-layer networks in unsupervised feature learning. In
Adam Coates, Andrew Ng, and Honglak Lee. 2011 · 2011
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Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition
Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel. 2012 · 2012
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Evaluation of information retrieval systems
Keneilwe Zuva and Tranos Zuva. 2012 · 2012
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Explaining and harnessing adversarial examples
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014 · 2014
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ImageNet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael S. Bernstein, Alexander C. Berg, and Li Feifei. 2015 · 2015
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Defensive distillation is not robust to adversarial examples
Nicholas Carlini and David Wagner. 2016 · 2016
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Tom B. Brown, Dandelion Mané, Aurko Roy, Martín Abadi, and Justin Gilmer. 2017 · 2017
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu. 2017 · 2017
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Universal adversarial perturbations. In
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, and Pascal Frossard. 2017 · 2017
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Fast Feature Fool: A data independent approach to universal adversarial perturbations. In
Konda Reddy Mopuri, Utsav Garg, and R. Venkatesh Babu. 2017 · 2017
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To prune, or not to prune: exploring the efficacy of pruning for model compression
Michael Zhu and Suyog Gupta. 2017 · 2017
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Learning universal adversarial perturbations with generative models. In
Jamie Hayes and George Danezis. 2018 · 2018
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Lavan: Localized and visible adversarial noise. In
Danny Karmon, Daniel Zoran, and Yoav Goldberg. 2018 · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018 · 2018
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Modality-specific cross-modal similarity measurement with recurrent attention network
Yuxin Peng, Jinwei Qi, and Yuxin Yuan. 2018 · 2018
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Defending dnn adversarial attacks with pruning and logits augmentation. In
Siyue Wang, Xiao Wang, Shaokai Ye, Pu Zhao, and Xue Lin. 2018 · 2018
Cited alongside, same era.
Universal adversarial attacks on text classifiers. In
Melika Behjati, Seyed-Mohsen Moosavi-Dezfooli, Mahdieh Soleymani Baghshah, and Pascal Frossard. 2019 · 2019
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Uniter: Learning universal image-text representations
Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, and Jingjing Liu. 2019 · 2019
Cited alongside, same era.
Perceptual-sensitive gan for generating adversarial patches. In
Aishan Liu, Xianglong Liu, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie, and Dacheng Tao. 2019 · 2019
Cited alongside, same era.
Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks. In
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee. 2019 · 2019
Cited alongside, same era.
Align before fuse: Vision and language representation learning with momentum distillation. In
Junnan Li, Ramprasaath Selvaraju, Akhilesh Gotmare, Shafiq Joty, Caiming Xiong, and Steven Chu Hong Hoi. 2021 · 2021
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Learning transferable visual models from natural language supervision. In
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021 · 2021
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Lightningdot: Pre-training visual-semantic embeddings for real-time image-text retrieval. In
Siqi Sun, Yen-Chun Chen, Linjie Li, Shuohang Wang, Yuwei Fang, and Jingjing Liu. 2021 · 2021
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Multimodal contrastive training for visual representation learning. In
Xin Yuan, Zhe Lin, Jason Kuen, Jianming Zhang, Yilin Wang, Michael Maire, Ajinkya Kale, and Baldo Faieta. 2021 · 2021
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Pre-trained Adversarial Perturbations. In
Yuanhao Ban and Yinpeng Dong. 2022 · 2022
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Florian Tramer and Dan Boneh. 2019 · 2019
Cited alongside, same era.
Universal adversarial triggers for attacking and analyzing NLP
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, and Sameer Singh. 2019 · 2019
Cited alongside, same era.
Language models are few-shot learners. In
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Cited alongside, same era.
Universal adversarial attack via enhanced projected gradient descent. In
Yingpeng Deng and Lina J Karam. 2020 · 2020
Cited alongside, same era.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2020 · 2020
Cited alongside, same era.
Oscar: Object-semantics aligned pre-training for vision-language tasks. In
Xiujun Li, Xi Yin, Chunyuan Li, Pengchuan Zhang, Xiaowei Hu, Lei Zhang, Lijuan Wang, Houdong Hu, Li Dong, Furu Wei, Yejin Choi, and Jianfeng Gao. 2020 · 2020
Cited alongside, same era.
A self-supervised approach for adversarial robustness. In
Muzammal Naseer, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Fatih Porikli. 2020 · 2020
Cited alongside, same era.
SSLGuard: A Watermarking Scheme for Self-supervised Learning Pre-trained Encoders. In
Tianshuo Cong, Xinlei He, and Yang Zhang. 2022 · 2022
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Retrieve fast, rerank smart: Cooperative and joint approaches for improved cross-modal retrieval
Gregor Geigle, Jonas Pfeiffer, Nils Reimers, Ivan Vulić, and Iryna Gurevych. 2022 · 2022
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PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning. In
Hongbin Liu, Jinyuan Jia, and Neil Zhenqiang Gong. 2022 · 2022
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How Adversarial Robustness Transfers from Pre-training to Downstream Tasks
Laura Fee Nern and Yash Sharma. 2022 · 2022
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Cross-Lingual Cross-Modal Retrieval with Noise-Robust Learning. In
Yabing Wang, Jianfeng Dong, Tianxiang Liang, Minsong Zhang, Rui Cai, and Xun Wang. 2022 · 2022
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Zhixiong Zeng and Wenji Mao. 2022 · 2022
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Towards adversarial attack on vision-language pre-training models. In
Jiaming Zhang, Qi Yi, and Jitao Sang. 2022 · 2022
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Most and Least Retrievable Images in Visual-Language Query Systems. In
Liuwan Zhu, Rui Ning, Jiang Li, Chunsheng Xin, and Hongyi Wu. 2022 · 2022
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PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models against Adversarial Examples. In
Shengshan Hu, Junwei Zhang, Wei Liu, Junhui Hou, Minghui Li, Leo Yu Zhang, Hai Jin, and Lichao Sun. 2023 · 2023
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Enhancing Sentence Representation with Visually-supervised Multimodal Pre-training. In
Zhe Li, T. Yang Laurence, Xin Nie, BoCheng Ren, and Xianjun Deng. 2023 · 2023
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Adversarial Patch Attacks against Aerial Imagery Object Detectors
Guijian Tang, Tingsong Jiang, Weien Zhou, Chao Li, Wen Yao, and Yong Zhao. 2023 · 2023
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Downstream-agnostic Adversarial Examples. In
Ziqi Zhou, Shengshan Hu, Ruizhi Zhao, Qian Wang, Leo Yu Zhang, Junhui Hou, and Hai Jin. 2023 · 2023
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Badencoder: Backdoor attacks to pre-trained encoders in self-supervised learning. In
Jinyuan Jia, Yupei Liu, and Neil Zhenqiang Gong. 2022 · 2059
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EncoderMI: Membership inference against pre-trained encoders in contrastive learning. In
Hongbin Liu, Jinyuan Jia, Wenjie Qu, and Neil Zhenqiang Gong. 2021 · 2095
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