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Results: 11
Number of items: 11
  • Open Access
    Baan, J., ter Hoeve, M., van der Wees, M., Schuth, A., & de Rijke, M. (2019). Understanding Multi-Head Attention in Abstractive Summarization. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.1911.03898
  • Open Access
    Baan, J., ter Hoeve, M., van der Wees, M., Schuth, A., & de Rijke, M. (2019). Do Transformer Attention Heads Provide Transparency in Abstractive Summarization? In Proceedings of FACTS-IR 2019 ArXiv. https://arxiv.org/abs/1907.00570
  • 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
    van der Wees, M., Bisazza, A., & Monz, C. (2017). Dynamic Data Selection for Neural Machine Translation. In M. Palmer, R. Hwa, & S. Riedel (Eds.), The Conference on Empirical Methods in Natural Language Processing: proceedings of the conference : EMNLP 2017 : September 9-11, 2017, Copenhagen, Denmark (pp. 1400-1410). Association for Computational Linguistics. https://doi.org/10.18653/v1/D17-1147
  • Open Access
    van der Wees, M. E. (2017). What’s in a domain? Towards fine-grained adaptation for machine translation. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    van der Wees, M., Bisazza, A., & Monz, C. (2016). Measuring the Effect of Conversational Aspects on Machine Translation Quality. In Y. Matsumoto, & R. Prasad (Eds.), Proceedings of COLING 2016: technical papers: the 26th International Conference on Computational Linguistics : Osaka, Japan, December 11-17 2016 (pp. 2571-2581). The COLING 2016 Organizing Committee. http://aclweb.org/anthology/C16-1242
  • Open Access
    van der Wees, M., Bisazza, A., & Monz, C. (2016). A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation. In WNUT 2016 : the 2nd Workshop on Noisy User-generated Text: proceedings of the Workshop : December 11, 2016, Osaka, Japan (pp. 43-50). The COLING 2016 Organizing Committee. http://aclweb.org/anthology/W16-3908
  • Open Access
    van der Wees, M., Bisazza, A., & Monz, C. (2015). Translation Model Adaptation Using Genre-Revealing Text Features: abstract. 22. Abstract from 14th Dutch-Belgian Information Retrieval Workshop, Amsterdam, Netherlands. https://ilps.science.uva.nl/wp-content/uploads/sites/8/2015/11/DIR2015-proceedings.pdf
  • van der Wees, M., Bisazza, A., & Monz, C. (2015). Five Shades of Noise: Analyzing Machine Translation Errors in User-Generated Text. In W. Xu, B. Han, & A. Ritter (Eds.), ACL-IJCNLP 2015 : ACL 2015 Workshop on Noisy User-generated Text: proceedings of the workshop : July 31, 2015, Beijing, China (pp. 28-37). The Association for Computational Linguistics. http://www.aclweb.org/anthology/W/W15/W15-4304.pdf
  • van der Wees, M., Bisazza, A., & Monz, C. (2015). Translation Model Adaptation Using Genre-Revealing Text Features. In B. Webber, M. Carpuat, A. Popescu-Belis, & C. Hardmeier (Eds.), DiscoMT 2015 : Discourse in Machine Translation: proceedings of the workshop : 17 September 2015, Lisbon, Portugal (pp. 132-141). The Association for Computational Linguistics. http://www.aclweb.org/anthology/W/W15/W15-2518.pdf
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