Chatbot&QA with knowledge 总结

时间 2021-01-11

标签 conversation chatbot knowledge nlp 繁體版

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Chatbot&QA with knowledge 目前，chatbot&QA都很火，Neural network 模型已经可以进行很自然的对话交互了，在传统的seq2seq模型的基础上，近年来提出很多结合Knowledge的方式。本文就是总结了部分此方向的论文。所谓的Knowledge分为两种，knowledge base 和unstructured textual informati

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1. 【译】Deep Learning with Knowledge Graphs
2. DKT—Going Deeper with Deep Knowledge Tracing
3. Knowledge Distillation论文阅读（2）：Learning Efficient Object Detection Models with Knowledge Distillation
4. 【论文总结】Efficient Coflow Scheduling Without Prior Knowledge
5. 论文解读：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
6. Enriching BERT with Knowledge Graph Embeddings for Document Classification
7. Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph
8. 【论文精读】Knowledge Transfer with Jacobian Matching
9. Multi-Label Zero-Shot Learning with Structured Knowledge Graphs
10. 【PaperReading】Text Generation from Knowledge Graphs with Graph Transformers
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1. 【译】Deep Learning with Knowledge Graphs
2. DKT—Going Deeper with Deep Knowledge Tracing
3. Knowledge Distillation论文阅读（2）：Learning Efficient Object Detection Models with Knowledge Distillation
4. 【论文总结】Efficient Coflow Scheduling Without Prior Knowledge
5. 论文解读：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
6. Enriching BERT with Knowledge Graph Embeddings for Document Classification
7. Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph
8. 【论文精读】Knowledge Transfer with Jacobian Matching
9. Multi-Label Zero-Shot Learning with Structured Knowledge Graphs
10. 【PaperReading】Text Generation from Knowledge Graphs with Graph Transformers

>>更多相关文章<<