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174 Center for Research on Foundation Models (CRFM) Kevin Ellis, Catherine Wong, Maxwell I. Nye, Mathias Sablé-Meyer, Lucas Morales, Luke B. Hewitt, Luc Cary, Armando Solar-Lezama, and Joshua B. Tenenbaum. 2021. DreamCoder: bootstrapping inductive program synthesis with wake- sleep library learning. In PLDI ’21: 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, Virtual Event, Canada, June 20-25, 20211, Stephen N. Freund and Eran Yahav (Eds.). ACM, 835–850. https://doi.org/10.1145/3453483.3454080 Gamaleldin F Elsayed, Ian Goodfellow, and Jascha Sohl-Dickstein. 2018. Adversarial reprogramming of neural networks. arXiv preprint arXiv:1806.11146 (2018). Erich Elsen, Marat Dukhan, Trevor Gale, and Karen Simonyan. 2020. Fast Sparse ConvNets. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Daniel C Elton. 2020. Self-explaining AI as an alternative to interpretable AI. In International Conference on Artificial General Intelligence. Springer, 95–106. Emad Elwany, Dave Moore, and Gaurav Oberoi. 2019. Bert goes to law school: Quantifying the competitive advantage of access to large legal corpora in contract understanding. arXiv preprint arXiv:1911.00473 (2019). Douglas C. Engelbart. 1963. A Conceptual Framework for the Augmentation of Man’s Intellect. In Computer-supported cooperative work: a book of readings. David Freeman Engstrom, Daniel E Ho, Catherine M Sharkey, and Mariano-Florentino Cuéllar. 2020. Government by algorithm: Artificial intelligence in federal administrative agencies. NYU School of Law, Public Law Research Paper 20-54 (2020). Danielle Ensign, Sorelle A Friedler, Scott Neville, Carlos Scheidegger, and Suresh Venkatasubramanian. 2018. Runaway feedback loops in predictive policing. In Conference on Fairness, Accountability and Transparency. PMLR, 160–171. Kawin Ethayarajh, David Duvenaud, and Graeme Hirst. 2019. Understanding Undesirable Word Embedding Associations. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, 1696–1705. https://doi.org/10.18653/v1/P19-1166 Kawin Ethayarajh and Dan Jurafsky. 2020. Utility is in the Eye of the User: A Critique of NLP Leaderboards. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics, Online, 4846–4853. https://doi.org/10.18653/v1/2020.emnlp-main.393 Allyson Ettinger. 2020. What BERT Is Not: Lessons from a New Suite of Psycholinguistic Diagnostics for Language Models. Transactions of the Association for Computational Linguistics 8 (2020), 34–48. https://doi.org/10.1162/tacl_a_00298 Allyson Ettinger and Tal Linzen. 2016. Evaluating vector space models using human semantic priming results. In Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP. Association for Computational Linguistics, Berlin, Germany, 72–77. https://doi.org/10.18653/v1/W16-2513 Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, and Erich Elsen. 2020. Rigging the Lottery: Making All Tickets Winners. In Proceedings of the 37th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 119), Hal Daumé III and Aarti Singh (Eds.). PMLR, 2943–2952. Tom Everitt, Gary Lea, and Marcus Hutter. 2018. AGI safety literature review. arXiv preprint arXiv:1805.01109 (2018). Benjamin Eysenbach, Shixi
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