This paper proposes a dually interactive matching network (DIM) for presenting the personalities of dialogue agents in retrieval-based chatbots. This model develops from the interactive matching network (IMN) which models the matching degree between a context composed of multiple utterances and a response candidate. Compared with previous persona fusion approaches which enhance the representation of a context by calculating its similarity with a given persona, the DIM model adopts a dual matching architecture, which performs interactive matching between responses and contexts and between responses and personas respectively for ranking response candidates. Experimental results on PERSONA-CHAT dataset show that the DIM model outperforms its baseline model, i.e., IMN with persona fusion, by a margin of 14.5% and outperforms the current state-of-the-art model by a margin of 27.7% in terms of top-1 accuracy hits@1.
One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles
Renmin University of China（中国人民大学）；Beijing Key Laboratory of Big Data Management and Analysis Methods（大数据管理与分析方法北京市重点实验室）；Key Laboratory of Data Engineering and Knowledge Engineering, MOE（教育部数据工程与知识工程重点实验室）；Université de Montréal（蒙特利尔大学）
Learning Implicit User Profiles for Personalized Retrieval-Based Chatbot
Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学高瓴人工智能学院）；Beijing Key Laboratory of Big Data Management and Analysis Methods（大数据管理与分析方法北京市重点实验室）；Université de Montréal（蒙特利尔大学）
Pchatbot: A Large-Scale Dataset for Personalized Chatbot
Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学高瓴人工智能学院）；School of Information, Renmin University of China（中国人民大学信息学院）；Université de Montréal（蒙特利尔大学）
Dialogue History Matters! Personalized Response Selectionin Multi-turn Retrieval-based Chatbots
Wangxuan Institute of Computer Technology（王选计算机技术研究所）；Center for Data Science（数据科学中心）；Academy for Advanced Interdisciplinary Studies（前沿交叉学科研究院）；Peking University（北京大学）；Soochow University（苏州大学）；Gaoling School of Artificial Intelligence（高瓴人工智能学院）；Renmin University of China（中国人民大学）
MIRACLE: Towards Personalized Dialogue Generation with Latent-Space Multiple Personal Attribute Control
Huazhong University of Science and Technology（华中科技大学）；Ping An Property & Casualty Insurance Company of China, Ltd.（中国平安财产保险股份有限公司）；Beijing Institute of Technology（北京理工大学）；Brilliance Technology Co. Ltd.（华晨科技股份有限公司）
RAM2C: A Liberal Arts Educational Chatbot based on Retrieval-augmented Multi-role Multi-expert Collaboration
Center for Brain Inspired Computing Research (CBICR), Tsinghua University（清华大学脑启发计算研究中心）；Optical Memory National Engineering Research Center, Tsinghua University（清华大学光存储国家工程研究中心）；Tsinghua University-China Electronics Technology HIK Group Co. Joint Research Center for Brain-inspired Computing（清华大学-中国电子 hik 集团联合脑启发计算研究中心）；IDG/McGovern Institute for Brain Research, Tsinghua University（清华大学 IDG/麦戈文脑科学研究院）；Tsinghua University（清华大学）
Improving Personality Consistency in Conversation by Persona Extending
Huazhong University of Science and Technology（华中科技大学）；Alibaba Group（阿里巴巴集团）；Beijing Institute of Technology（北京理工大学）；Ping An Property & Casualty Insurance company of China, Ltd（中国平安财产保险股份有限公司）
PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory
University of Pennsylvania（宾夕法尼亚大学）；Massachusetts Institute of Technology（麻省理工学院）；University of Washington（华盛顿大学）；University of California Santa Barbara（加州大学圣巴巴拉分校）；Meta；University of Southern California（南加州大学）；University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）；Microsoft Corporation（微软公司）
