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arXiv · 2204.07237

Constructing Open Cloze Tests Using Generation and Discrimination Capabilities of Transformers

Mariano Felice·Shiva Taslimipoor·Paula Buttery
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Abstract

This paper presents the first multi-objective transformer model for constructing open cloze tests that exploits generation and discrimination capabilities to improve performance. Our model is further enhanced by tweaking its loss function and applying a post-processing re-ranking algorithm that improves overall test structure. Experiments using automatic and human evaluation show that our approach can achieve up to 82% accuracy according to experts, outperforming previous work and baselines. We also release a collection of high-quality open cloze tests along with sample system output and human annotations that can serve as a future benchmark.

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Mariano Felice, Shiva Taslimipoor, Paula Buttery. 2022-04-14. Constructing Open Cloze Tests Using Generation and Discrimination Capabilities of Transformers. https://arxiv.org/abs/2204.07237

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