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Mohd, Tauheed Khan
- A Comparative Study Of Text Comprehension In Ielts Reading Exam Using Gpt-3
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Authors
Affiliations
1 Dept. of Math and Computer Science, Augustana College, IL, US
2 School of Information Security and Applied Computing, Eastern Michigan University, Ypsilanti, MI, US
1 Dept. of Math and Computer Science, Augustana College, IL, US
2 School of Information Security and Applied Computing, Eastern Michigan University, Ypsilanti, MI, US
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 16, No 1 (2024), Pagination: 45-52Abstract
This paper discusses the capabilities and limitations of GPT-3 (0), a state-of-the-art language model, in the context of text understanding. We begin by describing the architecture and training process of GPT-3, and provide an overview of its impressive performance across a wide range of natural language processing tasks, such as language translation, question-answering, and text completion. Throughout this research project, a summarizing tool was also created to help us retrieve content from any types of document, specifically IELTS (0) Reading Test data in this project. We also aimed to improve the accuracy of the summarizing, as well as question-answering capabilities of GPT-3 (0) via long text.Keywords
GPT, Artificial Intelligence, Natural language processing.Full Text
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