Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks

时间 2021-03-13

标签 Paper NLP NLG 繁體版

原文原文链接

Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks Abstract 对于开放域对话系统来说在小数据集上训练生成模型是一件比较困难的事情。已经存在的meta-learning，它通过在非目标任务上进行预训练然后在目标任务上进行参数微调。但是，微调从参数的角度区分了任务，但忽略了模型结构的，导致对

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1. Deep Reinforcement Learning for Dialogue Generation
2. Adversarial Learning for Neural Dialogue Generation 代码分析
3. Deep Reinforcement Learning for Dialogue Generation阅读笔记
4. 论文分享-- >Adversarial Learning for Neural Dialogue Generation
5. 论文阅读：Text-to-Text Pre-Training for Data-to-Text Tasks
6. Group-wise Contrastive Learning for Neural Dialogue Generation 阅读笔记
7. Deep Reinforcement Learning for Dialogue Generation 论文阅读 A Diversity-Promoting Objective Function fo
8. Tips for Generation in Encoder-Decoder model
9. EMNLP2020 | 近期必读Dialogue Generation精选论文
10. Learning Conditioned Graph Structures for Interpretable Visual Question Answering

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