The interest in Empathetic and Emotional Support conversations among the public has significantly increased. To offer more sensitive and understanding responses, leveraging commonsense knowledge has become a common strategy to better understand psychological aspects and causality. However, such commonsense inferences can be out of context and unable to predict upcoming dialogue themes, resulting in responses that lack coherence and empathy. To remedy this issue, we present Prophetic Commonsense Inference, an innovative paradigm for inferring commonsense knowledge. By harnessing the capabilities of Large Language Models in understanding dialogue and making commonsense deductions, we train tunable models to bridge the gap between past and potential future dialogues. Extensive experiments conducted on EmpatheticDialogues and Emotion Support Conversation show that equipping dialogue agents with our proposed prophetic commonsense inference significantly enhances the quality of their responses.

翻译：公众对共情和情感支持对话的兴趣显著增加。为了提供更敏感且更具理解性的回应，利用常识知识已成为一种常见策略，以更好地理解心理方面和因果关系。然而，此类常识推理可能脱离语境，无法预测即将到来的对话主题，导致回应缺乏连贯性和同理心。为解决这一问题，我们提出了预言性常识推理（Prophetic Commonsense Inference），这是一种用于推断常识知识的创新范式。通过利用大型语言模型在理解对话和进行常识演绎方面的能力，我们训练可调模型以弥合过去与潜在未来对话之间的差距。在EmpatheticDialogues和Emotion Support Conversation上进行的广泛实验表明，为对话代理配备我们提出的预言性常识推理显著提升了其回应的质量。