论文：Learning Matching Models with Weak Supervision for Response Selection in Retrieval-based Chatbots

时间 2020-01-22

标签论文 learning matching models weak supervision response selection retrieval based chatbots 繁體版

原文原文链接

论文连接：https://arxiv.org/abs/1805.02333app 本文提出了一种用seq2seq给每一个（context， response）pair打分，并把这个分数做为“soft” margin 用linear svm loss来进行训练的方法，有针对性地解决了当前训练检索式对话系统的matching model，在训练时sample negative responses的时候

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1. 检索式多轮对话系统论文：Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network 阅读笔记
2. 论文笔记——Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
3. 【论文阅读】Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval
4. 论文阅读：Instance Weighting in Dialogue Systems
5. Merging Weak and Active Supervision for Semantic Parsing论文笔记
6. Matching Networks for One Shot Learning论文解读
7. 论文《Matching Networks for One Shot Learning》阅读
8. Deep Learning for Chatbots, Part 2 – Implementing a Retrieval-Based Model in Tensorflow
9. [论文解读]Test Selection for Deep Learning Systems
10. Sequential Match Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Ch

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