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164 Center for Research on Foundation Models (CRFM) Andrea Bajcsy, Dylan P. Losey, M. O’Malley, and A. Dragan. 2017. Learning Robot Objectives from Physical Human Interaction. In Conference on Robot Learning (CORL). Bowen Baker, I. Kanitscheider, Todor Markov, Yi Wu, Glenn Powell, Bob McGrew, and Igor Mordatch. 2020. Emergent Tool Use From Multi-Agent Autocurricula. ArXiv abs/1909.07528 (2020). Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, and Ross Girshick. 2019. Phyre: A new benchmark for physical reasoning. Advances in Neural Information Processing Systems 32 (2019), 5082–5093. Jack Bandy and Nicholas Vincent. 2021. Addressing" Documentation Debt" in Machine Learning Research: A Retrospective Datasheet for BookCorpus. arXiv preprint arXiv:2105.05241 (2021). Kshitij Bansal, Sarah M. Loos, Markus N. Rabe, Christian Szegedy, and Stewart Wilcox. 2019. HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA (Proceedings of Machine Learning Research, Vol. 97), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 454–463. http://proceedings.mlr.press/v97/bansal19a.html Yamini Bansal, Gal Kaplun, and Boaz Barak. 2020. For self-supervised learning, Rationality implies generalization, provably. arXiv preprint arXiv:2010.08508 (2020). Elias Bareinboim, Juan D. Correa, Duligur Ibeling, and Thomas Icard. 2020. On Pearl’s Hierarchy and the Foundations of Causal Inference. Technical Report R-60. Causal AI Lab, Columbia University. Forthcoming in Probabilistic and Causal Inference: The Works of Judea Pearl (ACM Books). Solon Barocas, Kate Crawford, Aaron Shapiro, and Hanna Wallach. 2017. The Problem With Bias: Allocative Versus Representational Harms in Machine Learning. (2017). Talk at SIGCIS Conference. Marco Baroni. 2021. On the proper role of linguistically-oriented deep net analysis in linguistic theorizing. arXiv preprint arXiv:2106.08694 (2021). Christine Basta, Marta R Costa-Jussà, and Noe Casas. 2019. Evaluating the underlying gender bias in contextualized word embeddings. arXiv preprint arXiv:1904.08783 (2019). Priyam Basu, Tiasa Singha Roy, Rakshit Naidu, Zumrut Muftuoglu, Sahib Singh, and Fatemehsadat Mireshghallah. 2021. Benchmarking Differential Privacy and Federated Learning for BERT Models. arXiv preprint arXiv:2106.13973 (2021). Mary Bates. 2019. Health care chatbots are here to help. IEEE pulse 10, 3 (2019), 12–14. Sarah Batterbury. 2012. Language justice for Sign Language Peoples: The UN Convention on the Rights of Persons with Disabilities. Language Policy 11 (08 2012). https://doi.org/10.1007/s10993-012-9245-8 Herbert Bay, Tinne Tuytelaars, and Luc Van Gool. 2006. Surf: Speeded up robust features. In European conference on computer vision. Springer, 404–417. Daniel M Bear, Elias Wang, Damian Mrowca, Felix J Binder, Hsiau-Yu Fish Tung, RT Pramod, Cameron Holdaway, Sirui Tao, Kevin Smith, Li Fei-Fei, et al. 2021. Physion: Evaluating Physical Prediction from Vision in Humans and Machines. arXiv preprint arXiv:2106.08261 (2021). Adam L Beberg, Daniel L Ensign, Guha Jayachandran, Siraj Khaliq, and Vijay S Pande. 2009. Folding@home: Lessons from eight years of volunteer distributed computing. In 2009 IEEE International Symposium on Parallel & Distributed Processing. 1–8. J Thaddeus Beck, Melissa Rammage, Gretchen P Jackson, Anita M Preininger, Irene Da
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