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Results: 91
Number of items: 91
  • Open Access
    De Cao, N., Schlichtkrull, M., Aziz, W., & Titov, I. (2020). How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking. 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. 3243–3255). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.262
  • 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
    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
    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
    Emelin, D., Titov, I., & Sennrich, R. (2020). Detecting word sense disambiguation biases in machine translation for model-agnostic adversarial attacks. 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. 7635-7653). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.616
  • Open Access
    Kipf, T. N. (2020). Deep learning with graph-structured representations. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Le, P., & Titov, I. (2019). Distant Learning for Entity Linking with Automatic Noise Detection. 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. 4081-4090). The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1400
  • Open Access
    Emelin, D., Titov, I., & Sennrich, R. (2019). Widening the representation bottleneck in neural machine translation with lexical shortcuts. In O. Bojar, R. Chatterjee, C. Federmann, M. Fishel, Y. Graham, B. Haddow, M. Huck, A. Jimeno Yepes, P. Koehn, A. Martins, C. Monz, M. Negri, A. Névéol, M. Neves, M. Post, M. Turchi, & K. Verspoor (Eds.), Fourth Conference on Machine Translation - Proceedings of the Conference: WMT 2019 (Vol. 1, pp. 102-115). Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-5211
  • Open Access
    Voita, E., Talbot, D., Moiseev, F., Sennrich, R., & Titov, I. (2019). Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned. 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. 5797–5808). The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1580
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