Personalized Response Generation via Domain adaptation

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Transfer Learning in Natural Language Processing (2019, methodology): “…(Zoph et al., 2016; Yang et al., 2017; Wieting et al., 2016; Conneau et al., 2017; McCann et al., 2017) before turning to distant supervision approaches which use heuristics to automatically label datasets (Mintz et al., 2009; Severyn and Moschitti, 2015; Felbo et al., 2017; Yang et al., 2017).”
Challenges in Building Intelligent Open-domain Dialog Systems (2019, methodology): “Yang et al. [113] presented a transfer learning framework similar to Zhang et al. [120], but proposed to use a new adaptation mechanism based on reinforcement learning.”
Neural personalized response generation as domain adaptation (2017, methodology): “– NPM: a neural personalized model with domain adaptation for conversation generation, which is the most relevant work proposed by [46].”
Learning Personalized End-to-End Goal-Oriented Dialog (2018, background): “There are some researchers attempting to introduce personalized information to dialogs by transfer learning (Yang et (2017) add intermediate supervision to learn when to employ the user pro-ﬁle.”
Condition Aware and Revise Transformer for Question Answering (2020, background): “Yang et al. [33] and Zhang et al. [36] attempt to introduce personalized information to dialogs by transfer learning.”