| GPT-RE: In-context learning for relation extraction using large language models Z Wan, F Cheng, Z Mao, Q Liu, H Song, J Li, S Kurohashi EMNLP2023, 2023 | 176 | 2023 |
| CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark D Romero, C Lyu, HA Wibowo, T Lynn, I Hamed, AN Kishore, A Mandal, ... arXiv, 2024 | 24 | 2024 |
| Pre-training via leveraging assisting languages for neural machine translation H Song, R Dabre, Z Mao, F Cheng, S Kurohashi, E Sumita Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 14* | 2020 |
| Video-guided Machine Translation with Spatial Hierarchical Attention Network W Gu, H Song, C Chu, S Kurohashi ACL-IJCNLP 2021 Student Research Workshop, 2021 | 11 | 2021 |
| JASS: Japanese-specific sequence to sequence pre-training for neural machine translation Z Mao, F Cromieres, R Dabre, H Song, S Kurohashi Proceedings of the Twelfth Language Resources and Evaluation Conference, 2020 | 10 | 2020 |
| Relation extraction with weighted contrastive pre-training on distant supervision Z Wan, F Cheng, Q Liu, Z Mao, H Song, S Kurohashi EACL 2023 Findings, 2022 | 9 | 2022 |
| A system for worldwide covid-19 information aggregation A Aizawa, F Bergeron, J Chen, F Cheng, K Hayashi, K Inui, H Ito, ... 1st Workshop on NLP for COVID-19 at EMNLP 2020, 2020 | 9 | 2020 |
| Coursera Corpus Mining and Multistage Fine-Tuning for Improving Lectures Translation H Song, R Dabre, A Fujita, S Kurohashi Proceedings of the 12th Language Resources and Evaluation Conference, 3640-3649, 2020 | 9 | 2020 |
| Exploring the Impact of Layer Normalization for Zero-shot Neural Machine Translation Z Mao, R Dabre, Q Liu, H Song, C Chu, S Kurohashi Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 8 | 2023 |
| When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation? Z Mao, C Chu, R Dabre, H Song, Z Wan, S Kurohashi NAACL 2022 (Findings), 2022 | 6 | 2022 |
| BERTSeg: BERT Based Unsupervised Subword Segmentation for Neural Machine Translation H Song, R Dabre, Z Mao, C Chu, S Kurohashi AACL-IJCNLP, 2022 | 5 | 2022 |
| SelfSeg: A Self-supervised Sub-word Segmentation Method for Neural Machine Translation H Song, R Dabre, C Chu, S Kurohashi, E Sumita ACM Transactions on Asian and Low-Resource Language Information Processing …, 2023 | 4 | 2023 |
| Domain adaptation of neural machine translation through multistage fine-tuning H Song, R Dabre, A Fujita, S Kurohashi 26th Annual Conference of the Association for Natural Language Processing, 2020 | 4 | 2020 |
| Variable-length Neural Interlingua Representations for Zero-shot Neural Machine Translation Z Mao, H Song, R Dabre, C Chu, S Kurohashi Proceedings of the 1st International Workshop on Multilingual, Multimodal …, 2023 | 3 | 2023 |
| A FPGA friendly approximate computing framework with hybrid Neural networks H Song, X Song, T Li, N Jing, X Liang, L Jiang IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND …, 2018 | 3 | 2018 |
| NICT’s cascaded and end-to-end speech translation systems using whisper and IndicTrans2 for the Indic task R Dabre, H Song Proceedings of the 21st International Conference on Spoken Language …, 2024 | 2 | 2024 |
| Robust Neural Machine Translation for Abugidas by Glyph Perturbation H Kaing, C Ding, H Song, J Mao, H Tanaka, M Utiyama 言語処理学会 第30回年次大会, 560-565, 2024 | 2 | 2024 |
| Self-supervised Dynamic Programming Encoding for Neural Machine Translation H Song, R Dabre, C Chu, S Kurohashi, E Sumita 言語処理学会 第27回年次大会, 632-636, 2021 | 2 | 2021 |
| Energy-efficient and quality-assured approximate computing framework using a co-training method L Jiang, Z Song, H Song, C Xu, Q Xu, N Jing, W Zhang, X Liang ACM Transactions on Design Automation of Electronic Systems (TODAES) 24 (6 …, 2019 | 2 | 2019 |
| Invocation-driven neural approximate computing with a multiclass-classifier and multiple approximators H Song, C Xu, Q Xu, Z Song, N Jing, X Liang, L Jiang 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-8, 2018 | 2 | 2018 |
Sadao KurohashiKyoto UniversityAdresă de e-mail confirmată pe i.kyoto-u.ac.jp