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Results: 90
Number of items: 90
  • Open Access
    Zhang, B., Williams, P., Titov, I., & Sennrich, R. (2020). Improving massively multilingual neural machine translation and zero-shot translation. In D. Jurafsky, J. Chai, N. Schluter, & J. Tetreault (Eds.), The 58th Annual Meeting of the Association for Computational Linguistics: ACL 2020 : Proceedings of the Conference : July 5-10, 2020 (pp. 1628-1639). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.148
  • Open Access
    Zhang, B., Titov, I., Haddow, B., & Sennrich, R. (2020). Adaptive feature selection for end-to-end speech translation. In T. Cohn, Y. He, & Y. Liu (Eds.), Findings of the Association for Computational Linguistics : Findings of ACL: EMNLP 2020: 16-20 November, 2020 (pp. 2533-2544). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.findings-emnlp.230
  • Open Access
    Marcheggiani, D., & Titov, I. (2020). Graph convolutions over constituent trees for syntax-aware semantic role labeling. In B. Webber, T. Cohn, Y. He, & Y. Liu (Eds.), 2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020 (pp. 3915-3928). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.322
  • Open Access
    Zhao, Y., & Titov, I. (2020). Visually grounded compound PCFGs. In B. Webber, T. Cohn, Y. He, & Y. Liu (Eds.), 2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020 (pp. 4369-4379). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.354
  • Open Access
    Bastings, J. (2020). A tale of two sequences: Interpretable and linguistically-informed deep learning for natural language processing. [Thesis, fully internal, Universiteit van Amsterdam]. Institute for Logic, Language and Computation.
  • Open Access
    Kipf, T. N. (2020). Deep learning with graph-structured representations. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Wang, B., Titov, I., & Lapata, M. (2019). Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs. In K. Inui, J. Jiang, V. Ng, & X. Wan (Eds.), 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing: EMNLP-IJCNLP 2019 : proceedings of the conference : November 3-7, 2019, Hong Kong, China (pp. 3774-3785). The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1391
  • Open Access
    Bastings, J., Aziz, W., & Titov, I. (2019). Interpretable Neural Predictions with Differentiable Binary Variables. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 2963-2977). The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1284
  • Open Access
    Corro, C., & Titov, I. (2019). Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder. In ICLR 2019: International Conference on Learning Representations : New Orleans, Louisiana, United States, May 6-May 9, 2019 OpenReview. https://openreview.net/forum?id=BJlgNh0qKQ
  • Open Access
    Voita, E., Sennrich, R., & Titov, I. (2019). The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives. In K. Inui, J. Jiang, V. Ng, & X. Wan (Eds.), 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing: EMNLP-IJCNLP 2019 : proceedings of the conference : November 3-7, 2019, Hong Kong, China (pp. 4396-4406). The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1448
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