Conversational Agents (CAs) acting as peer supporters have been widely studied and demonstrated beneficial for people's mental health. However, previous peer support CAs either are user-initiated or follow predefined rules to initiate the conversations, which may discourage users to engage and build relationships with the CAs for long-term benefits. In this paper, we develop ComPeer, a generative CA that can proactively offer adaptive peer support to users. ComPeer leverages large language models to detect and reflect significant events in the dialogue, enabling it to strategically plan the timing and content of proactive care. In addition, ComPeer incorporates peer support strategies, conversation history, and its persona into the generative messages. Our one-week between-subjects study (N=24) demonstrates ComPeer's strength in providing peer support over time and boosting users' engagement compared to a baseline user-initiated CA.

翻译：作为同伴支持者的对话代理已被广泛研究，并证明对人们的心理健康有益。然而，以往的同伴支持对话代理要么由用户发起对话，要么遵循预定义规则来发起对话，这可能阻碍用户为获得长期益处而与对话代理建立关系并持续互动。本文开发了ComPeer，一种能够主动向用户提供适应性同伴支持的生成式对话代理。ComPeer利用大语言模型来检测并反映对话中的重要事件，使其能够策略性地规划主动关怀的时机与内容。此外，ComPeer将同伴支持策略、对话历史及其角色设定融入生成的消息中。我们为期一周的组间对照研究（N=24）表明，与基线用户发起式对话代理相比，ComPeer在提供长期同伴支持及提升用户参与度方面具有优势。