论文标题
使用变压器的产生和歧视能力构建开放式测试
Constructing Open Cloze Tests Using Generation and Discrimination Capabilities of Transformers
论文作者
论文摘要
本文介绍了第一个用于构建开放式披肩测试的多目标变压器模型，该模型利用发电和歧视能力来提高性能。通过调整其损耗函数并应用后处理的重新排列算法来进一步增强我们的模型，从而改善整体测试结构。使用自动和人类评估的实验表明，根据专家的说法，我们的方法最多可以达到82％的精度，表现优于先前的工作和基准。我们还发布了一系列高质量的开放式测试，以及样本系统输出和人类注释，可以用作未来的基准。
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.
