[38] Serhii Havrylov, German Kruszewski, and Armand Joulin. Cooperative learning of disjoint syntax and semantics. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 1118-1128, Minneapolis, Minnesota, June 2019. Association for Computational Linguistics. doi: 10.18653/v1/N19-1115. URL https://aclanthology.org/N19-1115.
[39] Sepp Hochreiter. Untersuchungen zu dynamischen neuronalen netzen. diploma thesis. Diploma thesis, TU Munich, 1991.
[40] Sepp Hochreiter and Jürgen Schmidhuber. Long short-term memory. Neural Comput., 9 (8):1735-1780, November 1997. ISSN 0899-7667. doi: 10.1162/neco.1997.9.8.1735. URL https://doi.org/10.1162/neco.1997.9.8.1735.
[41] Xiang Hu, Haitao Mi, Zujie Wen, Yafang Wang, Yi Su, Jing Zheng, and Gerard de Melo. R2D2: Recursive transformer based on differentiable tree for interpretable hierarchical language modeling. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 4897-4908, Online, August 2021. Association for Computational Linguistics. doi: 10.18653/v1/2021.acl-long.379. URL https://aclanthology.org/2021.acl-long.379.
[42] Xiang Hu, Haitao Mi, Liang Li, and Gerard de Melo. Fast-R2D2: A pretrained recursive neural network based on pruned CKY for grammar induction and text representation. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 2809-2821, Abu Dhabi, United Arab Emirates, December 2022. Association for Computational Linguistics. URL https://aclanthology.org/2022.emnlp-main.181.
[43] Weizhe Hua, Zihang Dai, Hanxiao Liu, and Quoc Le. Transformer quality in linear time. In Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvari, Gang Niu, and Sivan Sabato, editors, Proceedings of the 39th International Conference on Machine Learning, volume 162 of Proceedings of Machine Learning Research, pages 9099-9117. PMLR, 17-23 Jul 2022. URL https://proceedings.mlr.press/v162/hua22a.html.
[44] DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, and Behnam Neyshabur. Block-recurrent transformers. In Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems, 2022. URL https://openreview.net/forum?id=uloenYmLCAo.
[45] Eric Jang, Shixiang Gu, and Ben Poole. Categorical reparameterization with gumbel-softmax. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings. OpenReview.net, 2017. URL https://openreview.net/forum?id=rkE3y85ee.
[46] Da JU, Stephen Roller, Sainbayar Sukhbaatar, and Jason E Weston. Staircase attention for recurrent processing of sequences. In Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems, 2022. URL https://openreview.net/forum?id=NiCJDYpKaBj.
[47] Lukasz Kaiser, Aidan N. Gomez, and Francois Chollet. Depthwise separable convolutions for neural machine translation. In International Conference on Learning Representations, 2018. URL https://openreview.net/forum?id=S1jBcueAb.
[48] Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. A convolutional neural network for modelling sentences. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 655-665, Baltimore, Maryland, June 2014. Association for Computational Linguistics. doi: 10.3115/v1/P14-1062. URL https://www.aclweb.org/anthology/P14-1062.
[49] Divyansh Kaushik, Eduard Hovy, and Zachary Lipton. Learning the difference that makes a difference with counterfactually-augmented data. In International Conference on Learning Representations, 2020. URL https://openreview.net/forum?id=SklgssONFvr.