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基于RoBERTa的半监督分类

基于RoBERTa的半监督分类结合了大型预训练RoBERTa语言模型以及少量标记数据集和大量未标记文本。通过生成伪标签或在未标记样本上强制执行一致性，该方法从无标注数据中提取监督信号，在真实标签稀缺时产生更强的分类器。

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基于RoBERTa的半监督分类

[需翻译标题：BERT-based Classi…RoBERTa-based 分类微调基于RoBERTa的分类半监督式BERT分类半监督式 Transformer 弱监督 RoBERTa 分类

来源

Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019). RoBERTa: A Robustly Optimized BERT Pretraining Approach. arXiv preprint arXiv:1907.11692. link ↗
Xie, Q., Dai, Z., Hovy, E., Luong, M.-T., & Le, Q. V. (2020). Unsupervised Data Augmentation for Consistency Training. Advances in Neural Information Processing Systems (NeurIPS), 33, 11904–11915. link ↗

如何引用本页

ScholarGate. (2026, June 3). Semi-supervised RoBERTa-based Text Classification. ScholarGate. https://scholargate.app/zh/deep-learning/semi-supervised-roberta-based-classification

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弱监督 RoBERTa 分类

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