
This research introduces a novel approach to improve Grammatical Error Correction (GEC) in code-switched text by leveraging Large Language Models (LLMs) to generate synthetic training data, leading to the development of a GEC system specifically tailored for the increasingly common linguistic phenomenon of code-switching.


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improving-grammatical-error-correction-in-code-switched-text-using-llm-based-synthetic-data-generation


Improving Grammatical Error Correction in Code-Switched Text Using LLM-Based Synthetic Data Generation


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Developing effective grammatical error correction (GEC) systems for code-switched text by learners of English through synthetic data generation and linguistic insights.


improving-grammatical-error-correction-for-code-switched-sentences-by-learners-of-english


Improving Grammatical Error Correction for Code-Switched Sentences by Learners of English
