research-article

COSPLAY: Concept Set Guided Personalized Dialogue Generation Across Both Party Personas

Authors:

Chuangbai XiaoAuthors Info & Claims

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 201 - 211

https://doi.org/10.1145/3477495.3531957

Published: 07 July 2022 Publication History

Abstract

Maintaining a consistent persona is essential for building a human-like conversational model. However, the lack of attention to the partner makes the model more egocentric: they tend to show their persona by all means such as twisting the topic stiffly, pulling the conversation to their own interests regardless, and rambling their persona with little curiosity to the partner. In this work, we propose COSPLAY(COncept Set guided PersonaLized dialogue generation Across both partY personas) that considers both parties as a "team": expressing self-persona while keeping curiosity toward the partner, leading responses around mutual personas, and finding the common ground. Specifically, we first represent self-persona, partner persona and mutual dialogue all in the concept sets. Then, we propose the Concept Set framework with a suite of knowledge-enhanced operations to process them such as set algebras, set expansion, and set distance. Based on these operations as medium, we train the model by utilizing 1) concepts of both party personas, 2) concept relationship between them, and 3) their relationship to the future dialogue. Extensive experiments on a large public dataset, Persona-Chat, demonstrate that our model outperforms state-of-the-art baselines for generating less egocentric, more human-like, and higher quality responses in both automatic and human evaluations.

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Cited By

Xu ZChen DKuang JYi ZLi YShen YHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support ConversationProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657695(774-784)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657695
Su YBian HFan BLian BZhang CZhang BHuang R(2024)RLCA: Reinforcement Learning Model Integrating Cognition and Affection for Empathetic Response GenerationIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.325874111:1(1158-1168)Online publication date: Feb-2024
https://doi.org/10.1109/TCSS.2023.3258741
Kosenko DZharikova D(2024)KRGP: Knowledge-Based Response Generation with PersonaJournal of Mathematical Sciences10.1007/s10958-024-07432-2Online publication date: 11-Nov-2024
https://doi.org/10.1007/s10958-024-07432-2
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Index Terms

COSPLAY: Concept Set Guided Personalized Dialogue Generation Across Both Party Personas
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
    2. Natural language processing
      1. Discourse, dialogue and pragmatics
      2. Natural language generation
2. Information systems
  1. Information retrieval
    1. Users and interactive retrieval
      1. Personalization

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Information & Contributors

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Published In

cover image ACM Conferences

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2022

3569 pages

ISBN:9781450387323

DOI:10.1145/3477495

General Chairs:
Enrique Amigo
UNED
,
Pablo Castells
UAM and Amazon
,
Julio Gonzalo
UNED
,
Program Chairs:
Ben Carterette
Spotify
,
J. Shane Culpepper
RMIT University
,
Gabriella Kazai
Waseda University

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Published: 07 July 2022

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SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 11 - 15, 2022

Madrid, Spain

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Cited By

Xu ZChen DKuang JYi ZLi YShen YHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support ConversationProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657695(774-784)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657695
Su YBian HFan BLian BZhang CZhang BHuang R(2024)RLCA: Reinforcement Learning Model Integrating Cognition and Affection for Empathetic Response GenerationIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.325874111:1(1158-1168)Online publication date: Feb-2024
https://doi.org/10.1109/TCSS.2023.3258741
Kosenko DZharikova D(2024)KRGP: Knowledge-Based Response Generation with PersonaJournal of Mathematical Sciences10.1007/s10958-024-07432-2Online publication date: 11-Nov-2024
https://doi.org/10.1007/s10958-024-07432-2
Li JLi JSu Y(2024)A Map of Exploring Human Interaction Patterns with LLM: Insights into Collaboration and CreativityArtificial Intelligence in HCI10.1007/978-3-031-60615-1_5(60-85)Online publication date: 29-Jun-2024
https://dl.acm.org/doi/10.1007/978-3-031-60615-1_5
颜永(2023)Research on Generative Dialogue System Based on Reinforcement LearningHans Journal of Data Mining10.12677/HJDM.2023.13201813:02(185-193)Online publication date: 2023
https://doi.org/10.12677/HJDM.2023.132018
Wang FYin YHuang FWu K(2023)Please don't answer out of context: Personalized Dialogue Generation Fusing Persona and Context2023 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN54540.2023.10191649(1-8)Online publication date: 18-Jun-2023
https://doi.org/10.1109/IJCNN54540.2023.10191649

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