Large Language Models (LLMs) are increasingly being used to provide support and advice in personal domains such as romantic relationships, yet little is known about user perceptions of this type of advice. This study investigated how people evaluate advice on LLM-generated romantic relationships. Participants rated advice satisfaction, model reliability, and helpfulness, and completed pre- and post-measures of their general attitudes toward LLMs. Overall, the results showed participants' high satisfaction with LLM-generated advice. Greater satisfaction was, in turn, strongly and positively associated with their perceptions of the models' reliability and helpfulness. Importantly, participants' attitudes toward LLMs improved significantly after exposure to the advice, suggesting that supportive and contextually relevant advice can enhance users' trust and openness toward these AI systems.

翻译：大型语言模型（LLMs）正日益被用于提供恋爱关系等个人领域的支持与建议，然而用户对此类建议的感知尚不明确。本研究探讨了人们对LLM生成的恋爱关系建议的评价。参与者对建议满意度、模型可靠性和帮助性进行了评分，并在接触建议前后完成了对LLM总体态度的测量。总体而言，结果显示参与者对LLM生成建议的满意度较高。更高的满意度进而与他们对模型可靠性和帮助性的感知呈显著正相关。值得注意的是，参与者在接触建议后对LLM的态度显著改善，这表明具有支持性且情境相关的建议能够增强用户对这些人工智能系统的信任与接纳度。