DivTOD: Unleashing the Power of LLMs for Diversifying Task-Oriented Dialogue Representations

arXiv:2404.00557v1 Announce Type: new
Abstract: Language models pre-trained on general text have achieved impressive results in diverse fields. Yet, the distinct linguistic characteristics of task-oriented dialogues (TOD) compared to general text limit the practical utility of existing language models. Current task-oriented dialogue pre-training methods overlook the one-to-many property of conversations, where multiple responses can be appropriate given the same conversation context. In this paper, we propose a novel dialogue pre-training model called DivTOD, which collaborates with LLMs to learn diverse …

abstract arxiv cs.cl current dialogue diverse fields general language language models llms power practical pre-training property results text training type utility