Machine learningDeep learning / NLP / CV
弱监督文本摘要
弱监督文本摘要训练抽象式或抽取式摘要模型，无需人工标注的参考摘要。它不依赖昂贵的人工标签，而是利用启发式规则、远程监督、噪声自动标签或自监督目标等弱信号，来指导序列到序列模型或Transformer模型生成连贯、简洁的输入文档摘要。
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Method map
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来源
- Amplayo, R. K., & Lapata, M. (2020). Unsupervised Opinion Summarization with Noisy Autoencoder. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 1934–1945. link ↗
- Huang, L., Wu, L., & Wang, L. (2020). Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 5094–5107. link ↗
如何引用本页
ScholarGate. (2026, June 3). Weakly Supervised Text Summarization. ScholarGate. https://scholargate.app/zh/deep-learning/weakly-supervised-text-summarization
Which method?
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