| Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing P Liu, W Yuan, J Fu, Z Jiang, H Hayashi, G Neubig ACM computing surveys 55 (9), 1-35, 2023 | 5072 | 2023 |
| CodeGen: An Open Large Language Model for Code with Multi-turn Program Synthesis E Nijkamp, B Pang, H Hayashi, L Tu, H Wang, Y Zhou, S Savarese, ... arXiv preprint arXiv:2203.13474, 2022 | 1173* | 2022 |
| GSum: A General Framework for Guided Neural Abstractive Summarization ZY Dou, P Liu, H Hayashi, Z Jiang, G Neubig NAACL 2021, 4830-4842, 2020 | 270 | 2020 |
| CodeGen2: Lessons for Training LLMs on Programming and Natural Languages E Nijkamp, H Hayashi, C Xiong, S Savarese, Y Zhou arXiv preprint arXiv:2305.02309, 2023 | 190 | 2023 |
| WikiAsp: A Dataset for Multi-domain Aspect-based Summarization H Hayashi, P Budania, P Wang, C Ackerson, R Neervannan, G Neubig Transactions of the Association for Computational Linguistics 9, 211-225, 2021 | 76 | 2021 |
| Learning to Describe Unknown Phrases with Local and Global Contexts S Ishiwatari, H Hayashi, N Yoshinaga, G Neubig, S Sato, M Toyoda, ... NAACL 2019, 3467-3476, 2019 | 66 | 2019 |
| Latent Relation Language Models H Hayashi, Z Hu, C Xiong, G Neubig AAAI 2020, 7911-7918, 2020 | 46 | 2020 |
| Eve: A gradient based optimization method with locally and globally adaptive learning rates H Hayashi, J Koushik, G Neubig arXiv preprint arXiv:1611.01505, 2016 | 44* | 2016 |
| Inhibition of choroidal fibrovascular membrane formation by new class of RNA interference therapeutic agent targeting periostin T Nakama, S Yoshida, K Ishikawa, Y Kobayashi, Y Zhou, S Nakao, ... Gene therapy 22 (2), 127-137, 2015 | 41 | 2015 |
| Xgen-7b technical report E Nijkamp, T Xie, H Hayashi, B Pang, C Xia, C Xing, J Vig, S Yavuz, ... arXiv preprint arXiv:2309.03450, 2023 | 30 | 2023 |
| Findings of the Third Workshop on Neural Generation and Translation H Hayashi, Y Oda, A Birch, I Konstas, A Finch, MT Luong, G Neubig, ... WNGT 2019, 2019 | 30 | 2019 |
| DEEP: denoising entity pre-training for neural machine translation J Hu, H Hayashi, K Cho, G Neubig arXiv preprint arXiv:2111.07393, 2021 | 24 | 2021 |
| Findings of the Fourth Workshop on Neural Generation and Translation K Heafield, H Hayashi, Y Oda, I Konstas, A Finch, G Neubig, X Li, A Birch WNGT 2020, 1-9, 2020 | 18 | 2020 |
| Gemv2: Multilingual nlg benchmarking in a single line of code S Gehrmann, A Bhattacharjee, A Mahendiran, A Wang, A Papangelis, ... arXiv preprint arXiv:2206.11249, 2022 | 16 | 2022 |
| What's New? Summarizing Contributions in Scientific Literature H Hayashi, W Kryściński, B McCann, N Rajani, C Xiong EACL 2023, 2020 | 14 | 2020 |
| The ARIEL-CMU situation frame detection pipeline for LoReHLT16: a model translation approach P Littell, T Tian, R Xu, Z Sheikh, D Mortensen, L Levin, F Tyers, H Hayashi, ... Machine Translation 32, 105-126, 2018 | 11 | 2018 |
| Linguistic versus Latent Relations for Modeling Coherent Flow in Paragraphs D Kang, H Hayashi, AW Black, E Hovy EMNLP 2019, 2019 | 6 | 2019 |
| Systems and methods for a conversational framework of program synthesis H Hayashi, Y Zhou, P Bo, E Nijkamp US Patent 12,079,602, 2024 | 4 | 2024 |
| Neural Aspect-based Text Generation H Hayashi Carnegie Mellon University, 2021 | 1 | 2021 |
| Proceedings of the Fourth Workshop on Neural Generation and Translation A Birch, A Finch, H Hayashi, K Heafield, M Junczys-Dowmunt, I Konstas, ... Proceedings of the Fourth Workshop on Neural Generation and Translation, 2020 | 1 | 2020 |
Graham NeubigCarnegie Mellon University, All Hands AIPatvirtintas el. paštas cs.cmu.edu
