• Architecture

 
 

 
 

 
 

 
 

  • SemanticCaps

    通过Bi-LSTM表征得到的隐层向量经过multi-head后可以得到R个表征

     
     

     
     

 
 

  • DetectionCaps

    这部分和一般的胶囊网络一样，除了loss function中加入了self attention部分

     
     

     
     

     
     

     
     

     
     

 
 

 
 

  • Zero-shot DetectionCaps

 
 

基本过程和DetectionCaps很相似,计算DetectionCaps中已存在的existing intent和当前inference阶段emerging intent的相似度q,然后加权求和，squash后得到activation vector进行分类

 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

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