Fine-Tuning a Large Language Model with Reinforcement Learning for Educational Question Generation-Reference-Cited by-同舟云学术

Fine-Tuning a Large Language Model with Reinforcement Learning for Educational Question Generation

Published:2024 Issue: Volume: Page:424-438
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:en
Short-container-title:

Author:

Lamsiyah Salima^ORCID,El Mahdaouy Abdelkader^ORCID,Nourbakhsh Aria^ORCID,Schommer Christoph^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-64302-6_30

Reference34 articles.

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2. Chen, Y., Wu, L., Zaki, M.J.: Reinforcement learning based graph-to-sequence model for natural question generation. arXiv preprint arXiv:1908.04942 (2019)

3. Danon, G., Last, M.: A syntactic approach to domain-specific automatic question generation. arXiv preprint arXiv:1712.09827 (2017)

4. Das, B., Majumder, M., Phadikar, S., Sekh, A.A.: Automatic question generation and answer assessment: a survey. Res. Pract. Technol. Enhanc. Learn. 16(1), 1–15 (2021)

5. Du, X., Shao, J., Cardie, C.: Learning to ask: neural question generation for reading comprehension. In: Barzilay, R., Kan, M.Y. (eds.) Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1342–1352 (2017)

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