Machine learningDeep learning / NLP / CV
弱监督 Transformer
弱监督 Transformer 将 Transformer 架构的表征能力与利用嘈杂、不完整或程序化生成标签的弱监督策略相结合——当完全标注的数据集稀缺或成本高昂时，可以训练高质量的自然语言处理和视觉模型。
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Method map
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来源
- Ratner, A., Bach, S. H., Ehrenberg, H., Fries, J., Wu, S., & Re, C. (2017). Snorkel: Rapid training data creation with weak supervision. Proceedings of the VLDB Endowment, 11(3), 269–282. DOI: 10.14778/3157794.3157797 ↗
- Zhou, Z.-H. (2018). A brief introduction to weakly supervised learning. National Science Review, 5(1), 44–53. DOI: 10.1093/nsr/nwx106 ↗
如何引用本页
ScholarGate. (2026, June 3). Weakly Supervised Transformer. ScholarGate. https://scholargate.app/zh/deep-learning/weakly-supervised-transformer
Which method?
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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