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On the Opportunities and Risks of Foundation Models 213 Jakub Zavrel, Walter Daelemans, and Jorn Veenstra. 1997. Resolving PP attachment ambiguities with memory-based learning. In CoNLL97: Computational Natural Language Learning. Matthew D Zeiler and Rob Fergus. 2014. Visualizing and understanding convolutional networks. In European conference on computer vision. Springer, 818–833. Rowan Zellers, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019a. From Recognition to Cognition: Visual Commonsense Reasoning. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Rowan Zellers, Ari Holtzman, Matthew Peters, Roozbeh Mottaghi, Aniruddha Kembhavi, Ali Farhadi, and Yejin Choi. 2021a. PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World. arXiv preprint arXiv:2106.00188 (2021). Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi. 2019b. Defending Against Neural Fake News. In Advances in Neural Information Processing Systems (NeurIPS). 9054–9065. Rowan Zellers, Ximing Lu, Jack Hessel, Youngjae Yu, Jae Sung Park, Jize Cao, Ali Farhadi, and Yejin Choi. 2021b. MERLOT: Multimodal Neural Script Knowledge Models. arXiv preprint arXiv:2106.02636 (2021). Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, and Lucas Beyer. 2021. Scaling vision transformers. arXiv preprint arXiv:2106.04560 (2021). Haoran Zhang, Amy X Lu, Mohamed Abdalla, Matthew McDermott, and Marzyeh Ghassemi. 2020b. Hurtful words: quantifying biases in clinical contextual word embeddings. In proceedings of the ACM Conference on Health, Inference, and Learning. 110–120. Michael Zhang and Eunsol Choi. 2021. SituatedQA: Incorporating Extra-Linguistic Contexts into QA. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, Online and Punta Cana, Dominican Republic, 7371–7387. https://doi.org/10.18653/v1/2021.emnlp-main.586 T. Zhang and T. Hashimoto. 2020. On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies. In Association for Computational Linguistics (ACL). Tianyi Zhang and Tatsunori Hashimoto. 2021. On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies. arXiv preprint arXiv:2104.05694 (2021). Xingliang Zhang and Degan Shu. 2021. Current understanding on the Cambrian Explosion: questions and answers. Paläontologische Zeitschrift 95 (2021), 641–660. Yuhao Zhang, Hang Jiang, Yasuhide Miura, Christopher D Manning, and Curtis P Langlotz. 2020a. Contrastive learning of medical visual representations from paired images and text. arXiv preprint arXiv:2010.00747 (2020). Yuhui Zhang, Allen Nie, Ashley Zehnder, Rodney L Page, and James Zou. 2019b. VetTag: improving automated veterinary diagnosis coding via large-scale language modeling. NPJ digital medicine 2, 1 (2019), 1–8. Yian Zhang, Alex Warstadt, Haau-Sing Li, and Samuel R Bowman. 2021. When Do You Need Billions of Words of Pretraining Data?. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics. Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019a. ERNIE: Enhanced Language Representation with Informative Entities. In ACL. Zhoutong Zhang, Qiujia Li, Zhengjia Huang, Jiajun Wu, Joshua B Tenenbaum, and William T Freeman. 2017. Shape and material from sound. (2017). Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell, Vicente Ordonez,
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