A Diversity-Promoting Objective Function for Neural Conversation Models

时间 2020-08-08

标签 diversity promoting objective function neural conversation models 繁體版

原文原文链接

该论文提出了基于最大互信息（Maximum Mutual Information—MMI）的指望计算思想。web 传统的生成模型计算方式是：target = argmax（logP（T|S）），即在source给定的条件下，寻找出最大几率的target。这样的计算方式所带来的问题是会生成通常性的，具备大几率事件的target，失去了target的多样性。由互信息公式得：该论文基于MMI思想，

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1. A Diversity-Promoting Objective Function for Neural Conversation Models
2. A Diversity-Promoting Objective Function for Neural Conversation
3. A Diversity-Promoting Objective Function for Neural Conversation Models论文阅读
4. "A Diversity-Promoting Objective Function for Neural Conversation Models"阅读笔记
5. short text conversation: neural network
6. A Knowledge-Grounded Neural Conversation Model
7. lijiwei2-A Persona-Based Neural Conversation Model
8. A Knowledge-Grounded Neural Conversation Model 翻译
9. Deep Reinforcement Learning for Dialogue Generation 论文阅读 A Diversity-Promoting Objective Function fo
10. A Persona-Based Neural Conversation Model论文

>>更多相关文章<<