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ADL100(2)-Wuwei-检索式对话

作者:互联网

1. 检索

  1)(单轮回复选择)匹配模型

    a. sentence 生成定长向量 进行匹配 f(g(Q), g(R))

      f和g各种变种

      f: MLP Neural Tensor Cosine

      g: CNN LSTM+Att 

    b. query 与 candidate response 匹配

      g: Interaction Representation(Att / Sim)

    c. 效力和效率

  2)多轮回复选择

    a. 挑战:

      层次结构:word->utterance->session

      信息冗余

      逻辑:句子的顺序?词句长期依赖,适合句子的约束

  3)knowledge enhanced

  方向:deep wide pre-training ->  hhh yes

  Learning method

    from unlabelled data (weak supervision) (acl 18)

    denoise with Peer (co-teaching) (两个网络互相加权,互相trach acl19)

      teach with dynamic margin

      teach with dynamic instance weight

      teach with dynamic data curriculum(选高置信度的)

  Summary:

    matching model

    two framework

      vec -> match

      rep -> math -> aggregation

    external knowledge

    Deep, wide(better representation), learning method

   

    

标签:检索,wide,knowledge,dynamic,ADL100,Att,teach,Wuwei,method
来源: https://www.cnblogs.com/zh-liu/p/ADL100-2-Retrival-Chat.html