Triple Matching and Contrast Regularization Algorithm for Multiple Choices in Reading Comprehension
Multiple choice consists of three parts:article,question,and option.The main task is to find the correct option among multiple op-tions based on the article and question.Some algorithms have conducted some research on matching strategies between articles,questions,and options,but generally use paired processing or bidirectional matching methods,which cannot fully integrate articles,questions,and op-tions.To this end,a triple matching strategy(TM)is proposed,which uses contrastive regularization(CR)method to distinguish answers and matches any element of the article,question,and answer with other elements to absorb semantic information from the other two.Experiments have shown that capturing and strengthening the differences between correct and incorrect answers through CR can enable the model to better identify correct and incorrect answers,in order to provide reference and inspiration for researchers in this field.
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