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• W2963206148 abstract "Sequence-to-sequence neural network models for generation of conversational responses tend to generate safe, commonplace responses (e.g., I don’t know) regardless of the input. We suggest that the traditional objective function, i.e., the likelihood of output (response) given input (message) is unsuited to response generation tasks. Instead we propose using Maximum Mutual Information (MMI) as the objective function in neural models. Experimental results demonstrate that the proposed MMI models produce more diverse, interesting, and appropriate responses, yielding substantive gains in BLEU scores on two conversational datasets and in human evaluations." @default.
• W2963206148 created "2019-07-30" @default.
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• W2963206148 date "2016-01-01" @default.
• W2963206148 modified "2023-10-15" @default.
• W2963206148 title "A Diversity-Promoting Objective Function for Neural Conversation Models" @default.
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• W2963206148 doi "https://doi.org/10.18653/v1/n16-1014" @default.
• W2963206148 hasPublicationYear "2016" @default.
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