Weakly Supervised Context-based Interview Question Generation
Samiran Pal, Kaamraan Khan, Avinash Kumar Singh, Subhasish Ghosh, Tapas Nayak, Girish Palshikar, Indrajit Bhattacharya
Abstract
We explore the task of automated generation of technical interview questions from a given textbook. Such questions are different from those for reading comprehension studied in question generation literature. We curate a context based interview questions data set for Machine Learning and Deep Learning from two popular textbooks. We first explore the possibility of using a large generative language model (GPT-3) for this task in a zero shot setting. We then evaluate the performance of smaller generative models such as BART fine-tuned on weakly supervised data obtained using GPT-3 and hand-crafted templates. We deploy an automatic question importance assignment technique to figure out suitability of a question in a technical interview. It improves the evaluation results in many dimensions. We dissect the performance of these models for this task and also scrutinize the suitability of questions generated by them for use in technical interviews.- Anthology ID:
- 2022.gem-1.4
- Volume:
- Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Antoine Bosselut, Khyathi Chandu, Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, Yacine Jernite, Jekaterina Novikova, Laura Perez-Beltrachini
- Venue:
- GEM
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 43–53
- Language:
- URL:
- https://aclanthology.org/2022.gem-1.4
- DOI:
- 10.18653/v1/2022.gem-1.4
- Cite (ACL):
- Samiran Pal, Kaamraan Khan, Avinash Kumar Singh, Subhasish Ghosh, Tapas Nayak, Girish Palshikar, and Indrajit Bhattacharya. 2022. Weakly Supervised Context-based Interview Question Generation. In Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM), pages 43–53, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Weakly Supervised Context-based Interview Question Generation (Pal et al., GEM 2022)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/2022.gem-1.4.pdf