Следене
Chanjun Park
Chanjun Park
Research Professor at Korea University
Потвърден имейл адрес: korea.ac.kr - Начална страница
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Позовавания
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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
662023
Decoding strategies for improving low-resource machine translation
C Park, Y Yang, K Park, H Lim
Electronics 9 (10), 1562, 2020
482020
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
432021
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
352021
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
352021
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
342020
Ancient Korean neural machine translation
C Park, C Lee, Y Yang, H Lim
IEEE Access 8, 116617-116625, 2020
322020
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
242025
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
242021
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
192021
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
142022
Utilization strategy of user engagements in korean fake news detection
M Kang, J Seo, C Park, H Lim
IEEE Access 10, 79516-79525, 2022
132022
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
132021
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
132020
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
122022
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
122021
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