Generating Quizzes to Support Training on Quality Management and Assurance in Space Science and Engineering

October 07, 2022 ยท Declared Dead ยท ๐Ÿ› International Conference on Natural Language Generation

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Authors Andrรฉs Garcรญa-Silva, Cristian Berrรญo, Josรฉ Manuel Gรณmez-Pรฉrez arXiv ID 2210.03427 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 2 Venue International Conference on Natural Language Generation Last Checked 5 months ago
Abstract
Quality management and assurance is key for space agencies to guarantee the success of space missions, which are high-risk and extremely costly. In this paper, we present a system to generate quizzes, a common resource to evaluate the effectiveness of training sessions, from documents about quality assurance procedures in the Space domain. Our system leverages state of the art auto-regressive models like T5 and BART to generate questions, and a RoBERTa model to extract answers for such questions, thus verifying their suitability.
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