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208 Center for Research on Foundation Models (CRFM) Aäron van den Oord, S. Dieleman, H. Zen, K. Simonyan, Oriol Vinyals, A. Graves, Nal Kalchbrenner, A. Senior, and K. Kavukcuoglu. 2016. WaveNet: A Generative Model for Raw Audio. In SSW. Aäron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation Learning with Contrastive Predictive Coding. ArXiv abs/1807.03748 (2018). Aäron van den Oord, Oriol Vinyals, and K. Kavukcuoglu. 2017. Neural Discrete Representation Learning. In NIPS. Michael van Hartskamp, Sergio Consoli, Wim Verhaegh, Milan Petkovic, and Anja van de Stolpe. 2019. Artificial Intelligence in Clinical Health Care Applications: Viewpoint. Interactive Journal of Medical Research 8, 2 (Apr 2019), e12100. https: //doi.org/10.2196/12100 Marten van Schijndel and Tal Linzen. 2018. A Neural Model of Adaptation in Reading. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, Brussels, Belgium, 4704–4710. https://doi.org/10.18653/v1/D18-1499 Manasi Vartak, Harihar Subramanyam, Wei-En Lee, Srinidhi Viswanathan, Saadiyah Husnoo, Samuel Madden, and Matei Zaharia. 2016. ModelDB: a system for machine learning model management. In Proceedings of the Workshop on Human- In-the-Loop Data Analytics. 1–3. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention Is All You Need. arXiv preprint arXiv:1706.03762 (2017). Sara Veldhoen, Dieuwke Hupkes, and Willem Zuidema. 2016. Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure. In Pre-Proceedings of the Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo @ NIPS 2016). Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio. 2017. Graph Attention Networks. arXiv e-prints (2017), arXiv–1710. Pat Verga, Haitian Sun, Livio Baldini Soares, and William W Cohen. 2020. Facts as experts: Adaptable and interpretable neural memory over symbolic knowledge. arXiv preprint arXiv:2007.00849 (2020). Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, and Quoc Le. 2021. Towards domain-agnostic contrastive learning. In International Conference on Machine Learning. PMLR, 10530–10541. Lucas Nunes Vieira, Minako O’Hagan, and Carol O’Sullivan. 2020. Understanding the societal impacts of machine translation: a critical review of the literature on medical and legal use cases. Information, Communication & Society (2020), 1–18. Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Simas Sakenis, Jason Huang, Yaron Singer, and Stuart Shieber. 2020. Causal mediation analysis for interpreting neural NLP: The case of gender bias. arXiv preprint arXiv:2004.12265 (2020). Eduard Fosch Villaronga, Peter Kieseberg, and Tiffany Li. 2018. Humans forget, machines remember: Artificial intelligence and the right to be forgotten. Computer Law & Security Review 34, 2 (2018), 304–313. Pascal Vincent, Hugo Larochelle, Yoshua Bengio, , and Pierre-Antoine Manzagol. 2008. Extracting and Composing Robust Features with Denoising Autoencoders. In International Conference on Machine Learning (ICML). Antti Virtanen, Jenna Kanerva, Rami Ilo, Jouni Luoma, Juhani Luotolahti, Tapio Salakoski, Filip Ginter, and Sampo Pyysalo. 2019. Multilingual is not enough: BERT for Finnish. arXiv preprint arXiv:1912.07076 (2019). Rob Voigt, Nicholas P Camp, Vinodkumar P
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