| A survey of multilingual neural machine translation R Dabre, C Chu, A Kunchukuttan ACM Computing Surveys (CSUR) 53 (5), 1-38, 2020 | 390 | 2020 |
| An empirical comparison of domain adaptation methods for neural machine translation C Chu, R Dabre, S Kurohashi Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 246 | 2017 |
| Overview of the 8th workshop on Asian translation T Nakazawa, H Nakayama, C Ding, R Dabre, S Higashiyama, H Mino, ... Proceedings of the 8th Workshop on Asian Translation (WAT2021), 1-45, 2021 | 178 | 2021 |
| IndicBART: A pre-trained model for indic natural language generation R Dabre, H Shrotriya, A Kunchukuttan, R Puduppully, MM Khapra, ... arXiv preprint arXiv:2109.02903, 2021 | 103 | 2021 |
| Indictrans2: Towards high-quality and accessible machine translation models for all 22 scheduled indian languages J Gala, PA Chitale, R AK, V Gumma, S Doddapaneni, A Kumar, J Nawale, ... arXiv preprint arXiv:2305.16307, 2023 | 94* | 2023 |
| An empirical study of language relatedness for transfer learning in neural machine translation R Dabre, T Nakagawa, H Kazawa Proceedings of the 31st Pacific Asia conference on language, information and …, 2017 | 76 | 2017 |
| An empirical comparison of simple domain adaptation methods for neural machine translation C Chu, R Dabre, S Kurohashi arXiv preprint arXiv:1701.03214, 2017 | 74 | 2017 |
| Exploiting multilingualism through multistage fine-tuning for low-resource neural machine translation R Dabre, A Fujita, C Chu Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 72 | 2019 |
| Improving Transformer-Based Speech Recognition Systems with Compressed Structure and Speech Attributes Augmentation. S Li, R Dabre, X Lu, P Shen, T Kawahara, H Kawai Interspeech, 4400-4404, 2019 | 62 | 2019 |
| Recurrent stacking of layers for compact neural machine translation models R Dabre, A Fujita Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6292-6299, 2019 | 61 | 2019 |
| Exploiting out-of-domain parallel data through multilingual transfer learning for low-resource neural machine translation A Imankulova, R Dabre, A Fujita, K Imamura arXiv preprint arXiv:1907.03060, 2019 | 48 | 2019 |
| IndicNLG benchmark: Multilingual datasets for diverse NLG tasks in Indic languages A Kumar, H Shrotriya, P Sahu, R Dabre, R Puduppully, A Kunchukuttan, ... arXiv preprint arXiv:2203.05437, 2022 | 46 | 2022 |
| Enabling multi-source neural machine translation by concatenating source sentences in multiple languages R Dabre, F Cromieres, S Kurohashi arXiv preprint arXiv:1702.06135, 2017 | 38 | 2017 |
| Kyoto university participation to WAT 2016 F Cromieres, C Chu, T Nakazawa, S Kurohashi Proceedings of the 3rd Workshop on Asian Translation (WAT2016), 166-174, 2016 | 38 | 2016 |
| Leveraging small multilingual corpora for smt using many pivot languages R Dabre, F Cromieres, S Kurohashi, P Bhattacharyya Proceedings of the 2015 Conference of the North American Chapter of the …, 2015 | 37 | 2015 |
| Overview of the 10th workshop on Asian translation T Nakazawa, K Kinugawa, H Mino, I Goto, R Dabre, S Higashiyama, ... Proceedings of the 10th Workshop on Asian Translation, 1-28, 2023 | 32 | 2023 |
| Extremely low-resource neural machine translation for Asian languages R Rubino, B Marie, R Dabre, A Fujita, M Utiyama, E Sumita Machine Translation 34 (4), 347-382, 2020 | 28 | 2020 |
| Fusion of self-supervised learned models for MOS prediction Z Yang, W Zhou, C Chu, S Li, R Dabre, R Rubino, Y Zhao arXiv preprint arXiv:2204.04855, 2022 | 27 | 2022 |
| PUB: A Pragmatics Understanding Benchmark for Assessing LLMs’ Pragmatics Capabilities S Settaluri, M Doshi, PK Tankala, RM Venkataramana, R Dabre, ... Annual Meeting of the Association for Computational Linguistics, 2024 | 25* | 2024 |
| Cvqa: Culturally-diverse multilingual visual question answering benchmark D Romero, C Lyu, HA Wibowo, T Lynn, I Hamed, AN Kishore, A Mandal, ... arXiv preprint arXiv:2406.05967, 2024 | 24 | 2024 |
Chenhui ChuKyoto UniversityVerified email at i.kyoto-u.ac.jp
