Search results

    Filter results

  • Full text

  • Document type

  • Publication year

  • Organisation

Results: 90
Number of items: 90
  • Open Access
    Zhang, B., Titov, I., & Sennrich, R. (2021). On Sparsifying Encoder Outputs in Sequence-to-Sequence Models. In C. Zong, F. Xia, W. Li, & R. Navigli (Eds.), Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021: Findings of ACL: ACL-IJCNLP 2021 : August 1-6, 2021 (pp. 2888-2900). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.findings-acl.255
  • Open Access
    Wang, B., Lapata, M., & Titov, I. (2021). Learning from Executions for Semantic Parsing. In K. Toutanova, A. Rumshisky, L. Zettlemoyer, D. Hakkani-Tur, I. Beltagy, S. Bethard, R. Cotterell, T. Chakraborty, & Y. Zhou (Eds.), The 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: NAACL-HLT 2021 : proceedings of the conference : June 6-11, 2021 (pp. 2747-2759). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.naacl-main.219
  • Open Access
    Lyu, C., Cohen, S. B., & Titov, I. (2021). A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing. In M.-C. Moens, X. Huang, L. Specia, & S. W. Yih (Eds.), 2021 Conference on Empirical Methods in Natural Language Processing: EMNLP 2021 : proceedings of the conference : November 7-11, 2021 (pp. 9075-9091). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.emnlp-main.714
  • 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
    Hu, Z., Havrylov, S., Titov, I., & Cohen, S. B. (2020). Obfuscation for privacy-preserving syntactic parsing. In G. Bouma, Y. Matsumoto, S. Oepen, K. Sagae, D. Seddah, W. Sun, A. Søgaard, R. Tsarfaty, & D. Zeman (Eds.), The 16th International Conference on Parsing Technologies and IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies: IWPT 2020 : Proceedings of the Conference : July 9, 2020 (pp. 62-72). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.iwpt-1.7
  • Open Access
    Zhang, B., Titov, I., & Sennrich, R. (2020). Fast Interleaved Bidirectional Sequence Generation. In L. Barrault, O. Bojar, F. Bougares, R. Chatterjee, M. R. Costa-Jussà, C. Federmann, M. Fishel, A. Fraser, Y. Graham, P. Guzman, B. Haddow, M. Huck, A. Jimeno Yepes, P. Koehn, A. Martins, M. Morishita, C. Monz, M. Nagata, T. Nakazawa, & M. Negri (Eds.), Fifth Conference on Machine Translation : proceedings of the conference: EMNLP : November 19-20, 2020, online (pp. 503-518). Association for Computational Linguistics. https://aclanthology.org/2020.wmt-1.62
  • 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
    Bražinskas, A., Lapata, M., & Titov, I. (2020). Few-shot learning for opinion summarization. In B. Webber, T. Cohn, Y. Ye, & Y. Liu (Eds.), 2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020 (pp. 4119-4135). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.337
  • 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
Page 4 of 9