| Solar 10.7 b: Scaling large language models with simple yet effective depth up-scaling D Kim, C Park, S Kim, W Lee, W Song, Y Kim, H Kim, Y Kim, H Lee, J Kim, ... NAACL 2024 - Industry, 2024 | 142* | 2024 |
| A survey on evaluation metrics for machine translation S Lee, J Lee, H Moon, C Park, J Seo, S Eo, S Koo, H Lim Mathematics 11 (4), 1006, 2023 | 66 | 2023 |
| Decoding strategies for improving low-resource machine translation C Park, Y Yang, K Park, H Lim Electronics 9 (10), 1562, 2020 | 48 | 2020 |
| BTS: Back TranScription for Speech-to-Text Post-Processor using Text-to-Speech-to-Text C Park, J Seo, S Lee, C Lee, H Moon, S Eo, H Lim ACL 2021 - Proceedings of the 8th Workshop on Asian Translation (WAT2021), 2021 | 43 | 2021 |
| A Study on the Performance Improvement of Machine Translation Using Public Korean-English Parallel Corpus C Park, H Lim Journal of Digital Convergence 18 (6), 271-277, 2020 | 38* | 2020 |
| Neural spelling correction: translating incorrect sentences to correct sentences for multimedia C Park, K Kim, YW Yang, M Kang, H Lim Multimedia Tools and Applications 80, 34591-34608, 2021 | 35 | 2021 |
| Should we find another model?: Improving neural machine translation performance with ONE-piece tokenization method without model modification C Park, S Eo, H Moon, HS Lim NAACL 2021: Industry Papers, 97-104, 2021 | 35 | 2021 |
| Comparison of the evaluation metrics for neural grammatical error correction with overcorrection C Park, Y Yang, C Lee, H Lim IEEE Access 8, 106264-106272, 2020 | 34 | 2020 |
| Ancient Korean neural machine translation C Park, C Lee, Y Yang, H Lim IEEE Access 8, 116617-116625, 2020 | 32 | 2020 |
| sDPO: Don't Use Your Data All at Once D Kim, Y Kim, W Song, H Kim, Y Kim, S Kim, C Park COLING 2025 - Industry, 2025 | 24 | 2025 |
| Exploring the data efficiency of cross-lingual post-training in pretrained language models C Lee, K Yang, T Whang, C Park, A Matteson, H Lim Applied Sciences 11 (5), 1974, 2021 | 24 | 2021 |
| Comparative analysis of current approaches to quality estimation for neural machine translation S Eo, C Park, H Moon, J Seo, H Lim Applied Sciences 11 (14), 6584, 2021 | 19 | 2021 |
| A study on performance improvement considering the balance between corpus in Neural Machine Translation C Park, K Park, H Moon, S Eo, HS Lim Journal of the Korea Convergence Society 12 (5), 23-29, 2021 | 17* | 2021 |
| Open Ko-LLM Leaderboard: Evaluating Large Language Models in Korean with Ko-H5 Benchmark C Park, H Kim, D Kim, S Cho, S Kim, S Lee, Y Kim, H Lee ACL 2024, 2024 | 16* | 2024 |
| A dog is passing over the jet? a text-generation dataset for korean commonsense reasoning and evaluation J Seo, S Lee, C Park, Y Jang, H Moon, S Eo, S Koo, HS Lim Findings of the Association for Computational Linguistics: NAACL 2022, 2233-2249, 2022 | 14 | 2022 |
| Utilization strategy of user engagements in korean fake news detection M Kang, J Seo, C Park, H Lim IEEE Access 10, 79516-79525, 2022 | 13 | 2022 |
| An empirical study on automatic post editing for neural machine translation H Moon, C Park, S Eo, J Seo, H Lim IEEE Access 9, 123754-123763, 2021 | 13 | 2021 |
| Quality, not Quantity? : Effect of parallel corpus quantity and quality on Neural Machine Translation C Park, Y Lee, C Lee, HS Lim The 32st Annual Conference on Human & Cognitive Language Technology, 2020 | 13 | 2020 |
| AI for patents: A novel yet effective and efficient framework for patent analysis J Son, H Moon, J Lee, S Lee, C Park, W Jung, H Lim IEEE Access 10, 59205-59218, 2022 | 12 | 2022 |
| Filter-mBART Based Neural Machine Translation Using Parallel Corpus Filtering H Moon, C Park, S Eo, JB Park, HS Lim Korea Convergence Society 12 (5), 1-7, 2021 | 12 | 2021 |
Heuiseok LImProfessor at Computer science & eng., Korea Universityยืนยันอีเมลแล้วที่ korea.ac.kr