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Results: 160
Number of items: 160
  • Open Access
    Soleimani, A., Monz, C., & Worring, M. (2019). BERT for Evidence Retrieval and Claim Verification. ArXiv. https://arxiv.org/abs/1910.02655
  • Open Access
    Pei, J., Ren, P., Monz, C., & de Rijke, M. (2019). Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation. (v1 ed.) ArXiv. https://arxiv.org/abs/1911.08151
  • Open Access
    Jiang, S., Ren, P., Monz, C., & de Rijke, M. (2019). Improving Neural Response Diversity with Frequency-Aware Cross-Entropy Loss. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 2879-2885). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313415
  • Open Access
    Fadaee, M., & Monz, C. (2018). Back-Translation Sampling by Targeting Difficult Words in Neural Machine Translation. In E. Riloff, D. Chiang, J. Hockenmaier, & J. Tsujii (Eds.), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018: Brussels, Belgium, Oct. 31-Nov. 4 (pp. 436-446). The Association for Computational Linguistics. https://doi.org/10.18653/v1/D18-1040
  • Open Access
    Fadaee, M., Bisazza, A., & Monz, C. (2018). Examining the Tip of the Iceberg: A Data Set for Idiom Translation. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), LREC 2018 : Eleventh International Conference on Language Resources and Evaluation: May 7-12, 2018, Miyazaki, Japan (pp. 925-929). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2018/summaries/432.html
  • Open Access
    van der Wees, M., Bisazza, A., & Monz, C. (2018). Evaluation of Machine Translation Performance Across Multiple Genres and Languages. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), LREC 2018 : Eleventh International Conference on Language Resources and Evaluation: May 7-12, 2018, Miyazaki, Japan (pp. 3822-3827). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2018/summaries/853.html
  • Open Access
    Tran, K., Bisazza, A., & Monz, C. (2018). The Importance of Being Recurrent for Modeling Hierarchical Structure. In E. Riloff, D. Chiang, J. Hockenmaier, & J. Tsujii (Eds.), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018: Brussels, Belgium, Oct. 31-Nov. 4 (pp. 4731–4736). The Association for Computational Linguistics. https://doi.org/10.18653/v1/D18-1503
  • Open Access
    Tran, K. (2018). Predicting and discovering linguistic structure with neural networks. [Thesis, fully internal, Universiteit van Amsterdam].
  • Ghader, H., & Monz, C. (2017). What does Attention in Neural Machine Translation Pay Attention to? In G. Kondrak, & T. Watanabe (Eds.), The Eight International Joint Conference on Natural Language Processing: proceedings of the Conference : November 27-December 1, 2017, Taipei, Taiwan (Vol. 1, pp. 30-39). Asian Federation of Natural Language Processing. http://www.aclweb.org/anthology/I17-1004
  • Open Access
    Garmash, E. (2017). Exploring the correspondence between languages for machine translation. [Thesis, fully internal, Universiteit van Amsterdam].
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