Transforming online grammar education: Integrating GETN V2 and RoBERTa embeddings for effective English grammar correction

The increasing demand for intelligent language learning systems, traditional grammar correction models often fail to capture the complex syntactic dependencies and contextual nuances present in learner-generated texts. These limitations hinder accurate detection and correction of grammatical errors...

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Détails bibliographiques

Auteur principal:	Yining Du
Format:	Artigo
Langue:	Inglês
Publié:	Elsevier 2025-10-01
Collection:	Alexandria Engineering Journal
Sujets:	Grammar correction RoBERTa embeddings GETN Syntactic dependency parsing Graph neural networks Transformer architecture
Accès en ligne:	http://www.sciencedirect.com/science/article/pii/S1110016825009330
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