This study explores the proactive ability of LLMs to seek user support. We propose metrics to evaluate the trade-off between performance improvements and user burden, and investigate whether LLMs can determine when to request help under varying information availability. Our experiments show that without external feedback, many LLMs struggle to recognize their need for user support. The findings highlight the importance of external signals and provide insights for future research on improving support-seeking strategies. Source code: https://github.com/appier-research/i-need-help

翻译：本研究探讨了大语言模型主动寻求用户支持的能力。我们提出了评估性能提升与用户负担之间权衡的指标，并研究了大语言模型在不同信息可用性条件下能否自主判断何时需要请求帮助。实验表明，在没有外部反馈的情况下，许多大语言模型难以识别自身对用户支持的需求。这些发现凸显了外部信号的重要性，并为未来改进求助策略的研究提供了见解。源代码：https://github.com/appier-research/i-need-help