ZORA Publikationsliste

Publikationen

• 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 4387–4397. https://www.aclweb.org/anthology/D19-1448.pdf
• Voita, E., Sennrich, R., & Titov, I. (2019). Context-Aware Monolingual Repair for Neural Machine Translation 876–885. https://www.aclweb.org/anthology/D19-1081.pdf
• Tang, G., Sennrich, R., & Nivre, J. (2019). Encoders Help You Disambiguate Word Senses in Neural Machine Translation 1429–1435. https://doi.org/10.18653/v1/D19-1149
• Wetesko, J., Chochowski, M., Przybysz, P., Williams, P., Grundkiewicz, R., Sennrich, R., Haddow, B., Miceli Barone, A. V., & Birch, A. (2019, November 3). Samsung and University of Edinburgh’s System for the IWSLT 2019 16th International Workshop on Spoken Language Translation 2019, Hong Kong. https://doi.org/10.5281/zenodo.3525537
• Tang, G., Sennrich, R., & Nivre, J. (2019). Understanding Neural Machine Translation by Simplification: The Case of Encoder-free Models (G. Angelova, R. Mitkov, I. Nikolova, & I. Temnikova, Eds.; pp. 1186–1193). INCOMA. https://doi.org/10.26615/978-954-452-056-4_136
• Emelin, D., Titov, I., & Sennrich, R. (2019). Widening the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts 102–115. http://www.aclweb.org/anthology/W19-5211
• 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 5797–5808. https://www.aclweb.org/anthology/P19-1580
• Sennrich, R., & Zhang, B. (2019). Revisiting Low-Resource Neural Machine Translation: A Case Study 211–221. https://www.aclweb.org/anthology/P19-1021
• Zhang, B., & Sennrich, R. (2019). A Lightweight Recurrent Network for Sequence Modeling 1538–1548. https://www.aclweb.org/anthology/P19-1149
• Voita, E., Sennrich, R., & Titov, I. (2019). When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion 1198–1212. https://www.aclweb.org/anthology/P19-1116
• Läubli, S., Sennrich, R., & Volk, M. (2018). Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation 4791–4796. http://www.aclweb.org/anthology/D18-1512
• Tang, G., Müller, M., Rios, A., & Sennrich, R. (2018, November 4). Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures Conference on Empirical Methods in Natural Language Processing (EMNLP), Brussels. http://aclweb.org/anthology/D18-1458
• Rios, A., Müller, M., & Sennrich, R. (2018). The Word Sense Disambiguation Test Suite at WMT18 (No. 2). 594–602. https://doi.org/10.18653/v1/W18-6437
• Müller, M., Rios, A., Voita, E., & Sennrich, R. (2018). A Large-Scale Test Set for the Evaluation of Context-Aware Pronoun Translation 61–72. http://www.statmt.org/wmt18/pdf/WMT007.pdf
• Tang, G., Sennrich, R., & Nivre, J. (2018, November 1). An Analysis of Attention Mechanisms: The Case of Word Sense Disambiguation in Neural Machine Translation Proceedings of the Third Conference on Machine Translation, Brussels. http://www.statmt.org/wmt18/pdf/WMT004.pdf
• Voita, E., Serdyukov, P., Sennrich, R., & Titov, I. (2018). Context-Aware Neural Machine Translation Learns Anaphora Resolution 1264–1274. http://aclweb.org/anthology/P18-1117
• Bawden, R., Sennrich, R., Birch, A., & Haddow, B. (2018). Evaluating Discourse Phenomena in Neural Machine Translation 1304–1313. http://aclweb.org/anthology/N18-1118
• Rios, A., Mascarell, L., & Sennrich, R. (2017). Improving Word Sense Disambiguation in Neural Machine Translation with Sense Embeddings 11–19. http://www.aclweb.org/anthology/W17-4702
• Sennrich, R., Firat, O., Cho, K., Birch, A., Haddow, B., Hitschler, J., Junczys-Dowmunt, M., Läubli, S., Miceli Barone, A. V., Mokry, J., & Nădejde, M. (2017). Nematus: a Toolkit for Neural Machine Translation 65–68. https://doi.org/10.18653/v1/e17-3017
• Sennrich, R., & Kunz, B. (2014, May 31). Zmorge: A German Morphological Lexicon Extracted from Wiktionary Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14), Reykjavik. http://www.lrec-conf.org/proceedings/lrec2014/pdf/116_Paper.pdf

Seitennummerierung