Abstract:Automatic Short-Answer Grading (ASAG) is an application for recognizing textual entailment in smart education. With the continuous expansion of the application scope of artificial neural networks, many deep learning models have been applied to grading short-answer texts. However, the coding structures and interaction forms of existing models are still too simple to meet the requirements of the ASAG task, resulting in low scoring accuracy. To address these challenges, we propose a cross-lingual hybrid neural ne… Show more
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