Machine learningDeep learning / NLP / CV
自监督问答
自监督问答（Self-supervised Question Answering, SSQA）是一种训练范式，它利用未标记文本自动生成问答对——通过闭卷翻译、跨度掩码或神经问题生成——来训练问答模型，而无需任何人工标记数据。即使在标注数据集稀缺或特定领域的情况下，它也能实现高质量的阅读理解系统。
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来源
- Lewis, P., Denoyer, L., & Riedel, S. (2019). Unsupervised Question Answering by Cloze Translation. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), pp. 4896–4910. DOI: 10.18653/v1/P19-1484 ↗
- Alberti, C., Andor, D., Pitler, E., Devlin, J., & Collins, M. (2019). Synthetic QA Corpora Generation with Roundtrip Consistency. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), pp. 6168–6173. DOI: 10.18653/v1/p19-1620 ↗
如何引用本页
ScholarGate. (2026, June 3). Self-supervised Question Answering (SSQA). ScholarGate. https://scholargate.app/zh/deep-learning/self-supervised-question-answering
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