Report · Page 190

190
Center for Research on Foundation Models (CRFM)
Jindřich Libovick`y, Rudolf Rosa, and Alexander Fraser. 2019. How language-neutral is multilingual BERT? arXiv preprint
arXiv:1911.03310 (2019).
Opher Lieber, Or Sharir, Barak Lenz, and Yoav Shoham. 2021. Jurassic-1: Technical Details and Evaluation. White Paper.
AI21 Labs.
Chu-Cheng Lin, Aaron Jaech, Xin Li, Matt Gormley, and Jason Eisner. 2021. Limitations of Autoregressive Models and Their
Alternatives. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT). Online, 5147–5173. http://cs.jhu.edu/~jason/papers/#lin-et-al-
2021-naacl
Ro-Ting Lin, David C Christiani, Ichiro Kawachi, Ta-Chien Chan, Po-Huang Chiang, and Chang-Chuan Chan. 2016. Increased
risk of respiratory mortality associated with the high-tech manufacturing industry: A 26-Year study. International journal
of environmental research and public health 13, 6 (2016), 557.
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence
Zitnick. 2014. Microsoft coco: Common objects in context. In European conference on computer vision. Springer, 740–755.
Pantelis Linardatos, Vasilis Papastefanopoulos, and Sotiris Kotsiantis. 2021. Explainable AI: A Review of Machine Learning
Interpretability Methods. Entropy 23, 1 (2021), 18.
Linda L. Lindsey. 2015. The sociology of Gender Theoretical Perspectives and Feminist Frameworks. Routledge.
https:
//www.routledge.com/Gender-Sociological-Perspectives/Lindsey/p/book/9781138103696
Wang Ling, Edward Grefenstette, Karl Moritz Hermann, Tomáš Kočisk`y, Andrew Senior, Fumin Wang, and Phil Blunsom.
2016. Latent predictor networks for code generation. arXiv preprint arXiv:1603.06744 (2016).
Tal Linzen. 2020. How Can We Accelerate Progress Towards Human-like Linguistic Generalization?. In Proceedings of the
58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online,
5210–5217. https://doi.org/10.18653/v1/2020.acl-main.465
Tal Linzen and Marco Baroni. 2021. Syntactic structure from deep learning. Annual Review of Linguistics 7 (2021), 195–212.
Tal Linzen, Emmanuel Dupoux, and Yoav Goldberg. 2016. Assessing the ability of LSTMs to learn syntax-sensitive
dependencies. Transactions of the Association for Computational Linguistics (TACL) 4 (2016).
Marco Lippi, Przemysław Pałka, Giuseppe Contissa, Francesca Lagioia, Hans-Wolfgang Micklitz, Giovanni Sartor, and Paolo
Torroni. 2019. CLAUDETTE: an automated detector of potentially unfair clauses in online terms of service. Artificial
Intelligence and Law 27, 2 (2019), 117–139.
Zachary C. Lipton. 2018. The mythos of model interpretability. Commun. ACM 61, 10 (Sept. 2018), 36–43.
https:
//doi.org/10.1145/3233231
Zachary C. Lipton and Jacob Steinhardt. 2019. Troubling Trends in Machine Learning Scholarship: Some ML Papers
Suffer from Flaws That Could Mislead the Public and Stymie Future Research. Queue 17, 1 (Feb. 2019), 45–77. https:
//doi.org/10.1145/3317287.3328534
Andy T. Liu, Shuwen Yang, Po-Han Chi, Po-Chun Hsu, and Hung yi Lee. 2020d. Mockingjay: Unsupervised Speech
Representation Learning with Deep Bidirectional Transformer Encoders. ICASSP 2020 - 2020 IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP) (2020), 6419–6423.
Fenglin Liu, Shen Ge, and Xian Wu. 2021a. Competence-based Multimodal Curriculum Learnin