A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospects

Author:

Deng Yang1,Lei Wenqiang2,Lam Wai3,Chua Tat-Seng1

Affiliation:

1. National University of Singapore

2. Sichuan University

3. The Chinese University of Hong Kong

Abstract

Proactive dialogue systems, related to a wide range of real-world conversational applications, equip the conversational agent with the capability of leading the conversation direction towards achieving pre-defined targets or fulfilling certain goals from the system side. It is empowered by advanced techniques to progress to more complicated tasks that require strategical and motivational interactions. In this survey, we provide a comprehensive overview of the prominent problems and advanced designs for conversational agent's proactivity in different types of dialogues. Furthermore, we discuss challenges that meet the real-world application needs but require a greater research focus in the future. We hope that this first survey of proactive dialogue systems can provide the community with a quick access and an overall picture to this practical problem, and stimulate more progresses on conversational AI to the next level.

Publisher

International Joint Conferences on Artificial Intelligence Organization

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Large Language Model Powered Agents for Information Retrieval;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

2. Towards Human-centered Proactive Conversational Agents;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

3. Large Language Model Powered Agents in the Web;Companion Proceedings of the ACM Web Conference 2024;2024-05-13

4. Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive Dialogue;ACM Transactions on Information Systems;2024-04-27

5. TodBR: Target-Oriented Dialog with Bidirectional Reasoning on Knowledge Graph;Applied Sciences;2024-01-04

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