| Why self-attention? a targeted evaluation of neural machine translation architectures G Tang, M Müller, AR Gonzales, R Sennrich Proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 374 | 2018 |
| An analysis of attention mechanisms: The case of word sense disambiguation in neural machine translation G Tang, R Sennrich, J Nivre arXiv preprint arXiv:1810.07595, 2018 | 109 | 2018 |
| An evaluation of neural machine translation models on historical spelling normalization G Tang, F Cap, E Pettersson, J Nivre arXiv preprint arXiv:1806.05210, 2018 | 55 | 2018 |
| Encoders help you disambiguate word senses in neural machine translation G Tang, R Sennrich, J Nivre arXiv preprint arXiv:1908.11771, 2019 | 30 | 2019 |
| The Helsinki Neural Machine Translation System R Östling, Y Scherrer, J Tiedemann, G Tang, T Nieminen Proceedings of the Second Conference on Machine Translation, 338--347, 2017 | 22 | 2017 |
| Understanding neural machine translation by simplification: The case of encoder-free models G Tang, R Sennrich, J Nivre arXiv preprint arXiv:1907.08158, 2019 | 19 | 2019 |
| An unsupervised word sense disambiguation method based on sememe vector in HowNet G Tang, D Yu, E Xun J. Chin. Inf. Process 29 (6), 23-29, 2015 | 18* | 2015 |
| Why self-attention? A targeted evaluation of neural machine translation architectures. arXiv 2018 G Tang, M Müller, A Rios, R Sennrich arXiv preprint arXiv:1808.08946, 0 | 15 | |
| Revisiting negation in neural machine translation G Tang, P Rönchen, R Sennrich, J Nivre Transactions of the Association for Computational Linguistics 9, 740-755, 2021 | 13 | 2021 |
| Improving BERTScore for machine translation evaluation through contrastive learning G Tang, O Yousuf, Z Jin IEEE Access 12, 77739-77749, 2024 | 12 | 2024 |
| Understanding pure character-based neural machine translation: The case of translating Finnish into English G Tang, R Sennrich, J Nivre arXiv preprint arXiv:2011.03469, 2020 | 10 | 2020 |
| Chinese text simplification based on large language models H Huo, Z Fu, H Yu, S Yang, G Tang 2024 International Conference on Computational Linguistics and Natural …, 2024 | 6 | 2024 |
| Parallel data helps neural entity coreference resolution G Tang, C Hardmeier arXiv preprint arXiv:2305.17709, 2023 | 6 | 2023 |
| Can we neglect function words in word embedding? G Tang, G Rao, D Yu, E Xun International Conference on Computer Processing of Oriental Languages, 541-548, 2016 | 6 | 2016 |
| Why self-attention G Tang, M Müller, A Rios, R Sennrich A targeted evaluation of neural machine translation architectures. CoRR, abs, 1808 | 6 | 1808 |
| Proc. Conf. Empirical Methods Natural Lang. Process. G Tang, M Müller, A Rios, R Sennrich Proc. Conf. Empirical Methods Natural Lang. Process, 4263-4272, 2018 | 5 | 2018 |
| A hybrid re-ranking method for entity recognition and linking in search queries G Tang, Y Guo, D Yu, E Xun CCF International Conference on Natural Language Processing and Chinese …, 2015 | 4 | 2015 |
| 复杂科技术语构词中的语素化 于东， 饶高琦， 唐共波， 荀恩东 中国科技术语 17 (2), 15-20, 2015 | 4 | 2015 |
| Understanding Neural Machine Translation: An investigation into linguistic phenomena and attention mechanisms G Tang Acta Universitatis Upsaliensis, 2020 | 3 | 2020 |
| Research on keyword-based element extraction for Chinese patent retrieval Z Jin, Z Yang, G Tang, T Liu, E Xun 2024 International Conference on Asian Language Processing (IALP), 67-73, 2024 | 2 | 2024 |
Rico SennrichUniversity of ZurichVerified email at cl.uzh.ch
