Papers by Ujjwal Sharma

2 papers
Hi-GEC: Hindi Grammar Error Correction in Low Resource Scenario (2025.coling-main)

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Challenge: Automated Grammatical Error Correction (GEC) is a scarcely explored low-resource language . a recent study focused on English, but it focused on Hindi, which presents unique challenges due to its complex syntax and intricate morphology.
Approach: They propose to use a human-edited dataset to generate Hindi GEC data . they also investigate round trip translation using diverse languages for the technique .
Outcome: The proposed method outperforms other methods in Hindi, showing that it is highly efficient.
IndiGEC: Multilingual Grammar Error Correction for Low-Resource Indian Languages (2025.emnlp-main)

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Challenge: despite growing interest in GEC, most research has focused on English due to the lack of benchmark datasets for low-resource lan-guages.
Approach: They propose a new approach to generate high-quality synthetic data for GEC using monolingual corpora.
Outcome: The proposed framework outperforms other monolingual methods in English, Hindi, Bengali, Marathi, and Tamil.

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