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Exemplar Encoder-Decoder for Neural Conversation Generation
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
In this paper we present the Exemplar Encoder-Decoder network (EED), a novel conversation model that learns to utilize similar examples from training data to generate responses. Similar conversation examples (context-response pairs) from training data are retrieved using a traditional TF-IDF based retrieval model. The retrieved responses are used to create exemplar vectors that are used by the decoder to generate the response. The contribution of each retrieved response is weighed by thedoi:10.18653/v1/p18-1123 dblp:conf/acl/ContractorKJP18 fatcat:a4oro4lfivah3n4g7i2e4g4qsm