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对比学习在自然语言处理中的应用——通过对比学习文本表示

自然语言处理中的对比学习是一种表示学习技术——由SimCSE(Gao等,2021)和监督对比学习(Khosla等,2020)推广——通过将相似文本对的嵌入拉近,同时将不相似文本对的嵌入推远来训练文本编码器。其结果是一个密集、高质量的嵌入空间,该空间可以完全无监督地学习,或仅需少量监督即可学习,因此在标注数据稀缺时尤其有价值。

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Method map

The neighbourhood of related methods — select a node to explore.

对比学习在自然语言处理中的应用
BERT 嵌入自监督学习语义相似度文本分类

来源

  1. Gao, T., Yao, X., & Chen, D. (2021). SimCSE: Simple Contrastive Learning of Sentence Embeddings. Proceedings of EMNLP 2021. link
  2. Khosla, P., et al. (2020). Supervised Contrastive Learning. Advances in Neural Information Processing Systems (NeurIPS) 33. link

如何引用本页

ScholarGate. (2026, June 1). Contrastive Learning for Natural Language Processing. ScholarGate. https://scholargate.app/zh/text-mining/contrastive-learning-nlp

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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ScholarGateContrastive Learning for NLP (Contrastive Learning for Natural Language Processing). 于 2026-06-15 检索自 https://scholargate.app/zh/text-mining/contrastive-learning-nlp · 数据集: https://doi.org/10.5281/zenodo.20539026