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      Why Do Neural Dialog Systems Generate Short and Meaningless Replies? A Comparison between Dialog and Translation

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          Abstract

          This paper addresses the question: Why do neural dialog systems generate short and meaningless replies? We conjecture that, in a dialog system, an utterance may have multiple equally plausible replies, causing the deficiency of neural networks in the dialog application. We propose a systematic way to mimic the dialog scenario in a machine translation system, and manage to reproduce the phenomenon of generating short and less meaningful sentences in the translation setting, showing evidence of our conjecture.

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          Show and tell: A neural image caption generator

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            A Diversity-Promoting Objective Function for Neural Conversation Models

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              Neural Responding Machine for Short-Text Conversation

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                Author and article information

                Journal
                06 December 2017
                Article
                1712.02250
                532b53ab-2f0b-412e-aa73-3ac6de1ff7a6

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                cs.CL cs.LG

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