Pillars of Grammatical Error Correction: Comprehensive Inspection Of Contemporary Approaches In The Era of Large Language Models
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909178717536256 |
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| author | Omelianchuk, Kostiantyn Liubonko, Andrii Skurzhanskyi, Oleksandr Chernodub, Artem Korniienko, Oleksandr Samokhin, Igor |
| author_facet | Omelianchuk, Kostiantyn Liubonko, Andrii Skurzhanskyi, Oleksandr Chernodub, Artem Korniienko, Oleksandr Samokhin, Igor |
| contents | In this paper, we carry out experimental research on Grammatical Error Correction, delving into the nuances of single-model systems, comparing the efficiency of ensembling and ranking methods, and exploring the application of large language models to GEC as single-model systems, as parts of ensembles, and as ranking methods. We set new state-of-the-art performance with F_0.5 scores of 72.8 on CoNLL-2014-test and 81.4 on BEA-test, respectively. To support further advancements in GEC and ensure the reproducibility of our research, we make our code, trained models, and systems' outputs publicly available. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_14914 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Pillars of Grammatical Error Correction: Comprehensive Inspection Of Contemporary Approaches In The Era of Large Language Models Omelianchuk, Kostiantyn Liubonko, Andrii Skurzhanskyi, Oleksandr Chernodub, Artem Korniienko, Oleksandr Samokhin, Igor Computation and Language In this paper, we carry out experimental research on Grammatical Error Correction, delving into the nuances of single-model systems, comparing the efficiency of ensembling and ranking methods, and exploring the application of large language models to GEC as single-model systems, as parts of ensembles, and as ranking methods. We set new state-of-the-art performance with F_0.5 scores of 72.8 on CoNLL-2014-test and 81.4 on BEA-test, respectively. To support further advancements in GEC and ensure the reproducibility of our research, we make our code, trained models, and systems' outputs publicly available. |
| title | Pillars of Grammatical Error Correction: Comprehensive Inspection Of Contemporary Approaches In The Era of Large Language Models |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2404.14914 |