Machine learningDeep learning / NLP / CV
半监督问答
半监督问答（QA）在少量标记的问题-答案对上训练模型，然后在大型无标记语料库上生成伪标签并进行迭代再训练。这种自训练循环极大地增加了有效的训练数据，而无需完全手动标注的成本，在阅读理解、开放域问答和机器阅读任务上取得了强大的性能。
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来源
- Clark, K., Luong, M.-T., Le, Q. V., & Manning, C. D. (2020). ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. In Proceedings of ICLR 2020. link ↗
- Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R., & Le, Q. V. (2019). XLNet: Generalized Autoregressive Pretraining for Language Understanding. In Advances in Neural Information Processing Systems (NeurIPS 2019). link ↗
如何引用本页
ScholarGate. (2026, June 3). Semi-supervised Question Answering (Self-Training and Consistency-Based NLP). ScholarGate. https://scholargate.app/zh/deep-learning/semi-supervised-question-answering
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Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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