Instant-messaging human social chat typically progresses through a sequence of short messages. Existing step-by-step AI chatting systems typically split a one-shot generation into multiple messages and send them sequentially, but they lack an active waiting mechanism and exhibit unnatural message pacing. In order to address these issues, we propose Stephanie2, a novel next-generation step-wise decision-making dialogue agent. With active waiting and message-pace adaptation, Stephanie2 explicitly decides at each step whether to send or wait, and models latency as the sum of thinking time and typing time to achieve more natural pacing. We further introduce a time-window-based dual-agent dialogue system to generate pseudo dialogue histories for human and automatic evaluations. Experiments show that Stephanie2 clearly outperforms Stephanie1 on metrics such as naturalness and engagement, and achieves a higher pass rate on human evaluation with the role identification Turing test.

翻译：即时通讯中的人类社交对话通常通过一系列短消息逐步推进。现有的逐步AI聊天系统通常将一次性生成的内容拆分为多条消息并按顺序发送，但缺乏主动等待机制，且消息节奏呈现非自然特性。为解决这些问题，我们提出Stephanie2——一种新颖的下一代逐步决策对话智能体。通过主动等待与消息节奏自适应机制，Stephanie2在每一步明确决策发送或等待，并将延迟建模为思考时间与输入时间的总和，从而实现更自然的对话节奏。我们进一步引入基于时间窗口的双智能体对话系统，以生成用于人工与自动评估的伪对话历史。实验表明，Stephanie2在自然度、参与度等指标上显著优于Stephanie1，并在角色识别图灵测试的人类评估中获得了更高的通过率。