[1] Clarifai, https://www clarifai.com/. URL https://www clarifai.com/.
[2] Cohere, https://cohere.ai. URL https://cohere.ai/.
[3] Openai, https://openai.com. URL https://openai.com/.
[4] Poet2, https://labs.hyperledger.org/labs/archived/sawtooth-poet2.html. URL https://labs. hyperledger.org/labs/archived/sawtooth-poet2.html.
[5] Google, https://google.github.io/snappy/. URL https://google.github.io/snappy/.
[6] Facebook zstd, https://github.com/facebook/zstd. URL https://github.com/facebook/zstd.
[7] Yossi Adi, Carsten Baum, Moustapha Cisse, Benny Pinkas, and Joseph Keshet. Turning your weakness into a strength: Watermarking deep neural networks by backdooring. In 27th USENIX Security Symposium (USENIX Security 18), pages 1615-1631, 2018.
[8] Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B Brown, Dawn Song, Ulfar Erlingsson, et al. Extracting training data from large language models. In USENIX Security Symposium, volume 6, 2021.
[9] Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin. Emerging properties in self-supervised vision transformers. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pages 9650-9660, October 2021.
[10] Ting Chen, S. Kornblith, M. Norouzi, and G. Hinton. A simple framework for contrastive learning of visual representations. International Conference on Machine Learning, 2020.
[11] Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. A simple framework for contrastive learning of visual representations, 2020.
[12] Xinlei Chen and Kaiming He. Exploring simple siamese representation learning. 2020.
[13] Adam Coates, Andrew Ng, and Honglak Lee. An Analysis of Single Layer Networks in Unsupervised Feature Learning. In AISTATS, 2011. https://cs.stanford.edu/~acoates/papers/coatesleeng_aistats_2011.pdf.
[14] Tianshuo Cong, Xinlei He, and Yang Zhang. SsIguard: A watermarking scheme for self-supervised learning pre-trained encoders. CoRR, abs/2201.11692, 2022. URL https://arxiv.org/abs/2201.11692.
[15] Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. Imagenet: A large-scale hierarchical image database. In 2009 IEEE conference on computer vision and pattern recognition, pages 248–255. IEEE, 2009.
[16] Adam Dziedzic, Nikita Dhawan, Muhammad Ahmad Kaleem, Jonas Guan, and Nicolas Papernot. On the difficulty of defending self-supervised learning against model extraction. In International Conference on Machine Learning, 2022.
[17] Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem, Nikita Dhawan, Jonas Guan, Yannis Cattan, Franziska Boenisch, and Nicolas Papernot. Dataset inference for self-supervised models. In Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems, 2022. URL https://openreview.net/forum?id=CCBJf9xJo2X.
[18] Adam Dziedzic, Muhammad Ahmad Kaleem, Yu Shen Lu, and Nicolas Papernot. Increasing the cost of model extraction with calibrated proof of work. In International Conference on Learning Representations, 2022. URL https://arxiv.org/abs/2201.09243.
[19] Stefan Dziembowski, Sebastian Faust, Vladimir Kolmogorov, and Krzysztof Pietrzak. Proofs of space. 2013. URL https://eprint.iacr.org/2013/796. https://eprint.iacr.org/2013/796.