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On the Opportunities and Risks of Foundation Models 207 Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, and Phillip Isola. 2020a. What makes for good views for contrastive learning. arXiv preprint arXiv:2005.10243 (2020). Yuandong Tian, Lantao Yu, Xinlei Chen, and Surya Ganguli. 2020b. Understanding self-supervised learning with dual deep networks. arXiv preprint arXiv:2010.00578 (2020). Elizabeth Chika Tippett, Charlotte Alexander, and L Karl Branting. 2021. Does Lawyering Matter? Predicting Judicial Decisions from Legal Briefs, and What That Means for Access to Justice. Texas Law Review, Forthcoming (2021). Ilya Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, and Alexey Dosovitskiy. 2021. MLP-Mixer: An all-MLP Architecture for Vision. arXiv:2105.01601 [cs.CV] Nenad Tomasev, Kevin R. McKee, Jackie Kay, and Shakir Mohamed. 2021. Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities. arXiv:2102.04257 (2021). https://doi.org/10.1145/3461702.3462540 Christopher Tosh, Akshay Krishnamurthy, and Daniel Hsu. 2020. Contrastive estimation reveals topic posterior information to linear models. arXiv:2003.02234 (2020). Christopher Tosh, Akshay Krishnamurthy, and Daniel Hsu. 2021. Contrastive learning, multi-view redundancy, and linear models. In Algorithmic Learning Theory. PMLR, 1179–1206. Florian Tramèr and Dan Boneh. 2021. Differentially Private Learning Needs Better Features (or Much More Data). In International Conference on Learning Representations. Florian Tramèr, Fan Zhang, Ari Juels, Michael K. Reiter, and Thomas Ristenpart. 2016. Stealing machine learning models via prediction APIs. In USENIX Security. Nilesh Tripuraneni, Michael I Jordan, and Chi Jin. 2020. On the theory of transfer learning: The importance of task diversity. arXiv preprint arXiv:2006.11650 (2020). Megan L. Truax. 2018. The Impact of Teacher Language and Growth Mindset Feedback on Writing Motiva- tion. Literacy Research and Instruction 57, 2 (2018), 135–157. https://doi.org/10.1080/19388071.2017.1340529 arXiv:https://doi.org/10.1080/19388071.2017.1340529 Tomer Tsaban, Julia K Varga, Orly Avraham, Ziv Ben Aharon, Alisa Khramushin, and Ora Schueler-Furman. 2021. Harnessing protein folding neural networks for peptide-protein docking. bioRxiv (2021). Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, and Louis-Philippe Morency. 2020. Self-supervised learning from a multi-view perspective. arXiv preprint arXiv:2006.05576 (2020). Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, SM Eslami, Oriol Vinyals, and Felix Hill. 2021. Multimodal Few-Shot Learning with Frozen Language Models. arXiv preprint arXiv:2106.13884 (2021). Masatoshi Tsuchiya. 2018. Performance Impact Caused by Hidden Bias of Training Data for Recognizing Textual Entailment. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). European Language Resources Association (ELRA), Miyazaki, Japan. https://aclanthology.org/L18-1239 Lifu Tu, Garima Lalwani, Spandana Gella, and He He. 2020. An empirical study on robustness to spurious correlations using pre-trained language models. Transactions of the Association for Computational Linguistics 8 (2020), 621–633. Wenling Tu and Yujung Lee. 2009. Ineffective environmental laws in regulating electronic manufacturing pollution: Examining water pollution disp
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