Door-in-the-Face Requests and Refusal Behaviour in Large Language Models· 大型语言模型中的门面拒绝行为
Does the door-in-the-face technique work on language models? In humans, a large request that is refused makes a smaller follow-up request more likely to be granted. We test this on nine production models from three providers: each model refuses a large request, then receives a smaller version of the same request, and we compare its compliance with asking directly. The answer depends on the model. On Anthropic's frontier models the technique works: Opus 5 answers the smaller request 65.8% of the time after refusing the larger one, against 29.3% when asked directly. On the frontier models of OpenAI and Google, and on Haiku 4.5, it backfires, lowering compliance by 15.5 to 23.0 points. A control locates the effect: a refused large request on an unrelated topic does less than the related one o
研究大型语言模型中门面拒绝技巧的效果。
- 核心方法
- 对来自三家供应商的九个生产模型进行测试，先让模型拒绝一个大请求，再提出一个小请求，比较其接受率与直接提出小请求时的情况。
- 适合谁读
- 研究者、工程师、产品设计者
- 要解决的问题
- 探讨在大型语言模型中，先提出一个较大请求（被拒绝）是否能增加后续较小请求被接受的可能性。
- 关键实验
- 实验结果显示，Anthropic的前沿模型在此技巧下，小型请求的接受率为65.8%，而直接请求时为29.3%；OpenAI和Google的前沿模型及Haiku 4.5则表现出相反效果，接受率降低了15.5到23.0个百分点。
- 主要贡献
- 揭示了不同语言模型对门面拒绝技巧的响应差异，有助于理解模型的行为模式。
- 意义与局限
- 研究为理解人类与AI交互中的心理策略提供了参考，但不同模型的反应差异表明该技巧应用需谨慎。