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Neural Personalized Response Generation as Domain Adaptation

arXiv 1701.02073 ↗First posted 9 Jan 2017cs.CLcited by 19

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Abstract (arXiv)

In this paper, we focus on the personalized response generation for conversational systems. Based on the sequence to sequence learning, especially the encoder-decoder framework, we propose a two-phase approach, namely initialization then adaptation, to model the responding style of human and then generate personalized responses. For evaluation, we propose a novel human aided method to evaluate the performance of the personalized response generation models by online real-time conversation and offline human judgement. Moreover, the lexical divergence of the responses generated by the 5 personalized models indicates that the proposed two-phase approach achieves good results on modeling the responding style of human and generating personalized responses for the conversational systems.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jan 2017.

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Citing papers per year: 2021: 5; 2022: 5; 2023: 4; 2024: 3; 2025: 1; 2026: 1.

19 papers.

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  1. 2022Long Time No See! Open-Domain Conversation with Long-Term Persona Memorycited by 107
  2. 2025MemBench: Towards More Comprehensive Evaluation on the Memory of LLM-based Agentscited by 82
  3. 2024The Oscars of AI Theater: A Survey on Role-Playing with Language Modelscited by 47
  4. 2022On the Domain Adaptation and Generalization of Pretrained Language Models: A Surveycited by 22
  5. 2022Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characterscited by 16
  6. 2021Transferable Persona-Grounded Dialogues via Grounded Minimal Editscited by 10
  7. 2021A Cooperative Memory Network for Personalized Task-oriented Dialogue Systems with Incomplete User Profilescited by 8
  8. 2021Bilateral Personalized Dialogue Generation with Contrastive Learningcited by 8
  9. 2023Personalizing Task-oriented Dialog Systems via Zero-shot Generalizable Reward Functioncited by 7
  10. 2022COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendationcited by 6
  11. 2023A Survey of Personality, Persona, and Profile in Conversational Agents and Chatbotscited by 5
  12. 2021Attention-based Contextual Language Model Adaptation for Speech Recognitioncited by 4
7 more
  1. 2022Hierarchical Inductive Transfer for Continual Dialogue Learningcited by 3
  2. 2021Stylistic Retrieval-based Dialogue System with Unparallel Training Datacited by 2
  3. 2023User Persona Identification and New Service Adaptation Recommendationcited by 2
  4. 2023A Conditional Generative Chatbot using Transformer Modelcited by 0
  5. 2024A Stack-Propagation Framework for Low-Resource Personalized Dialogue Generationcited by 0
  6. 2024A Static and Dynamic Attention Framework for Multi Turn Dialogue Generationcited by 0
  7. 2026GRAG: Generic Response-Augmented Generation Framework for Personalized Conversational Systemscited by 0