Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation

Jian Wang, Yi Cheng, Dongding Lin, Chak Tou Leong, Wenjie Li
10/11/2023
cs.CLcs.AI

No official code found. Best implementation: iwangjian/TopDial (31 stars, Apache-2.0, last commit 2025-10-18).

Abstract

Target-oriented dialogue systems, designed to proactively steer conversations toward predefined targets or accomplish specific system-side goals, are an exciting area in conversational AI. In this work, by formulating a <dialogue act, topic> pair as the conversation target, we explore a novel problem of personalized target-oriented dialogue by considering personalization during the target accomplishment process. However, there remains an emergent need for high-quality datasets, and building one from scratch requires tremendous human effort. To address this, we propose an automatic dataset curation framework using a role-playing approach. Based on this framework, we construct a large-scale personalized target-oriented dialogue dataset, TopDial, which comprises about 18K multi-turn dialogues. The experimental results show that this dataset is of high quality and could contribute to exploring personalized target-oriented dialogue.

View on arXivView PDF

Code Implementations(1)

iwangjian/TopDialCommunity100%
Apache-2.0

[EMNLP 2023] Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation

311PythonJul 3, 20231 years agoApache-2.0
data-curationdialogue-systemspersonalization

Similar Papers

DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI

83% match1 repo5272023

Follow Me: Conversation Planning for Target-driven Recommendation Dialogue Systems

83% match1 repo122022

WHAT, WHEN, and HOW to Ground: Designing User Persona-Aware Conversational Agents for Engaging Dialogue

83% match2023

S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs

82% match2023

Knowledge-Grounded Conversational Data Augmentation with Generative Conversational Networks

82% match2022

SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents

82% match1 repo1.6k2026

Cite this paper

@article{wang2023targetoriented,
  title  = {Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation},
  author = {Jian Wang and Yi Cheng and Dongding Lin and Chak Tou Leong and Wenjie Li},
  year   = {2023},
  eprint = {2310.07397},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.07397v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2310.07397.svg)](https://codeofpaper.com/paper/2310.07397)

Discussion