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• W2950283666 abstract "We present open domain response generation with meta-words. A meta-word is a structured record that describes various attributes of a response, and thus allows us to explicitly model the one-to-many relationship within open domain dialogues and perform response generation in an explainable and controllable manner. To incorporate meta-words into generation, we enhance the sequence-to-sequence architecture with a goal tracking memory network that formalizes meta-word expression as a goal and manages the generation process to achieve the goal with a state memory panel and a state controller. Experimental results on two large-scale datasets indicate that our model can significantly outperform several state-of-the-art generation models in terms of response relevance, response diversity, accuracy of one-to-many modeling, accuracy of meta-word expression, and human evaluation." @default.
• W2950283666 created "2019-06-27" @default.
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• W2950283666 date "2019-06-14" @default.
• W2950283666 modified "2023-10-16" @default.
• W2950283666 title "Neural Response Generation with Meta-Words" @default.
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• W2950283666 doi "https://doi.org/10.48550/arxiv.1906.06050" @default.
• W2950283666 hasPublicationYear "2019" @default.
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