mlsanityData to 14 Oct 2026

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

arXiv 2210.03427 ↗First posted 7 Oct 2022cs.CL cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 3 references that are in the map. First posted on arXiv 7 Oct 2022.

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References · 3

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893

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