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Learning to Abstract for Memory augmented Conversational Response Generation

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Figure

Figure 1: An example of abstracting training corpusand memorizing their characteristics in the form of keyvectors and value vectors
Figure 2: The architecture of our model. Solid arrows show both the training and generation (testing) processes;dashed arrows show the training process
Table 1: The overall performance for all competing methods on quality, relevance, diversity and informativeness.
Table 3: The statistics on the size of memory slots(%|m|), cluster number (Cluster #), query number(Query #), and query proportion over all queries (Query) for the three memory slot types.
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