SubmissionNumber#=%=#90
FinalPaperTitle#=%=#CYUT at SemEval-2024 Task 7: A Numerals Augmentation and Feature Enhancement Approach to Numeral Reading Comprehension
ShortPaperTitle#=%=#
NumberOfPages#=%=#7
CopyrightSigned#=%=#Tsz-Yeung Lau
JobTitle#==#
Organization#==#Chaoyang University of Technology, 168, Jifeng E. Rd., Wufeng District, Taichung, 413310 Taiwan, R.O.C.
Abstract#==#This study explores Task 2 in NumEval-2024, which is SemEval-2024(Semantic Evaluation)Task 7 , focusing on the Reading Comprehension of Numerals in Text (Chinese). The datasetutilized in this study is the Numeral-related Question Answering Dataset (NQuAD), and the model employed is BERT. The data undergoes preprocessing, incorporating Numerals Augmentation and Feature Enhancement to numerical entities before model training. Additionally, fine-tuning will also be applied. The result was an accuracy rate of 77.09%, representing a 7.14% improvement compared to the initial NQuAD processing model, referred to as the Numeracy-Enhanced Model (NEMo).
Author{1}{Firstname}#=%=#Tsz-Yeung
Author{1}{Lastname}#=%=#Lau
Author{1}{Username}#=%=#anson70242
Author{1}{Email}#=%=#s10927116@gm.cyut.edu.tw
Author{1}{Affiliation}#=%=#Department of CSIE, Chaoyang University of Technology
Author{2}{Firstname}#=%=#Shih-Hung
Author{2}{Lastname}#=%=#Wu
Author{2}{Email}#=%=#shwu@cyut.edu.tw
Author{2}{Affiliation}#=%=#Department of CSIE, Chaoyang University of Technology

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