@inproceedings{felice-etal-2022-constructing,
    title = "Constructing Open Cloze Tests Using Generation and Discrimination Capabilities of Transformers",
    author = "Felice, Mariano  and
      Taslimipoor, Shiva  and
      Buttery, Paula",
    editor = "Muresan, Smaranda  and
      Nakov, Preslav  and
      Villavicencio, Aline",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2022",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.findings-acl.100/",
    doi = "10.18653/v1/2022.findings-acl.100",
    pages = "1263--1273",
    abstract = "This paper presents the first multi-objective transformer model for generating 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."
}