2017/06/09 by Qian Qiao, Qiao Qian, Minlie Huang +8 · 1 citation
Computer Science · Physics and Astronomy · #Authorship Attribution and Profiling #Computation and Language (cs.CL) #FOS: Computer and information sciences #Opinion Dynamics and Social Influence #Topic Modeling #cs.CL
paper · pdf · doi:10.48550/arxiv.1706.02861
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openalex publication_date 2017/06/09 · arxiv created 2017/06/21 · arxiv updated 2017/06/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Endowing a chatbot with personality or an identity is quite challenging but critical to deliver more realistic and natural conversations. In this paper, we address the issue of generating responses that are coherent to a pre-specified agent profile. We design a model consisting of three modules: a profile detector to decide whether a post should be responded using the profile and which key should be addressed, a bidirectional decoder to generate responses forward and backward starting from a selected profile value, and a position detector that predicts a word position from which decoding should start given a selected profile value. We show that general conversation data from social media can be used to generate profile-coherent responses. Manual and automatic evaluation shows that our model can deliver more coherent, natural, and diversified responses.