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On the Opportunities and Risks of Foundation Models 175 Anjalie Field, Su Lin Blodgett, Zeerak Waseem, and Yulia Tsvetkov. 2021. A Survey of Race, Racism, and Anti-Racism in NLP. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics, Online, 1905–1925. https://doi.org/10.18653/v1/2021.acl-long.149 Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. In International Conference on Machine Learning (ICML). Chelsea Finn and Sergey Levine. 2017. Deep visual foresight for planning robot motion. In International Conference on Robotics and Automation (ICRA). C. Finn, S. Levine, and P. Abbeel. 2016a. Guided cost learning: Deep inverse optimal control via policy optimization. In International Conference on Machine Learning (ICML). 49–58. Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, and Pieter Abbeel. 2016b. Deep spatial autoencoders for visuomotor learning. In 2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 512–519. Vlad Firoiu, Eser Aygün, Ankit Anand, Zafarali Ahmed, Xavier Glorot, Laurent Orseau, Doina Precup, and Shibl Mourad. 2021. Training a First-Order Theorem Prover from Synthetic Data. The First Mathematical Reasoning in General Artificial Intelligence Workshop, ICLR 2021 (2021). https://mathai-iclr.github.io/papers/papers/MATHAI_18_paper.pdf Jaime F. Fisac, Neil F. Lugovoy, Vicenç Rúbies Royo, S. Ghosh, and C. Tomlin. 2019. Bridging Hamilton-Jacobi Safety Analysis and Reinforcement Learning. In International Conference on Robotics and Automation (ICRA). Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, and Danqi Chen. 2019. MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension. In Workshop on Machine Reading for Question Answering (MRQA). Carlos Florensa, Yan Duan, and P. Abbeel. 2017. Stochastic Neural Networks for Hierarchical Reinforcement Learning. ArXiv abs/1704.03012 (2017). Luciano Floridi, Josh Cowls, Monica Beltrametti, Raja Chatila, Patrice Chazerand, Virginia Dignum, Christoph Luetge, Robert Madelin, Ugo Pagallo, Francesca Rossi, Burkhard Schafer, Peggy Valcke, and Effy Vayena. 2018. AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds and Machines 28, 4 (Nov. 2018), 689–707. https://doi.org/10.1007/s11023-018-9482-5 Ruth C. Fong and Andrea Vedaldi. 2017. Interpretable Explanations of Black Boxes by Meaningful Perturbation. In Proceedings of the IEEE International Conference on Computer Vision (ICCV). Stanislav Fort. 2021. Adversarial examples for the OpenAI CLIP in its zero-shot classification regime and their semantic generalization. https://stanislavfort.github.io/2021/01/12/OpenAI_CLIP_adversarial_examples.html S. Frank, Irene Fernandez Monsalve, Robin L. Thompson, and G. Vigliocco. 2013. Reading time data for evaluating broad- coverage models of English sentence processing. Behavior Research Methods 45 (2013), 1182–1190. Matt Fredrikson, Somesh Jha, and Thomas Ristenpart. 2015. Model inversion attacks that exploit confidence information and basic countermeasures. In ACM SIGSAC Conference on Computer and Communications Security. Jonathan B. Freeman, Andrew M. Penner, Aliya Saperstein, Matthias Scheutz, and Nalini Ambady. 2011. Looking th
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