A significant application of Large Language Models (LLMs), like ChatGPT, is their deployment as chat agents, which respond to human inquiries across a variety of domains. While current LLMs proficiently answer general questions, they often fall short in complex diagnostic scenarios such as legal, medical, or other specialized consultations. These scenarios typically require Task-Oriented Dialogue (TOD), where an AI chat agent must proactively pose questions and guide users toward specific goals or task completion. Previous fine-tuning models have underperformed in TOD and the full potential of conversational capability in current LLMs has not yet been fully explored. In this paper, we introduce DiagGPT (Dialogue in Diagnosis GPT), an innovative approach that extends LLMs to more TOD scenarios. In addition to guiding users to complete tasks, DiagGPT can effectively manage the status of all topics throughout the dialogue development. This feature enhances user experience and offers a more flexible interaction in TOD. Our experiments demonstrate that DiagGPT exhibits outstanding performance in conducting TOD with users, showing its potential for practical applications in various fields.

翻译：大语言模型（LLMs）如ChatGPT的重要应用之一是作为对话代理部署，可跨多个领域回应人类查询。尽管当前LLMs能熟练回答通用问题，但在法律、医疗或其他专业咨询等复杂诊断场景中往往表现不足。这类场景通常需要任务导向型对话（TOD），即AI对话代理需主动提问并引导用户实现特定目标或完成任务。以往的微调模型在TOD中表现欠佳，且当前LLMs的对话能力尚未被充分挖掘。本文提出DiagGPT（诊断对话GPT），这是一种创新方法，可将LLMs拓展至更多TOD场景。除引导用户完成任务外，DiagGPT还能有效管理对话发展过程中所有主题的状态。这一特性增强了用户体验，并在TOD中实现了更灵活的交互。实验表明，DiagGPT在引导用户进行TOD时表现出卓越性能，展示了其在各领域的实际应用潜力。