arXiv:2610.31946v1 Announce Type: new Abstract: Three students answered the same exam prompt by hand: "What is happiness? Are you happy?" Their ages, recorded at collection, are 17, 28, and 45. The 17-year-old's answer is hedged and formally phrased. Asked to match each answer to an age and gender label, most frontier language models confidently assign it to an adult. This paper reports a structured case study of that failure across six models: Claude Fable 5, Gemini 3.1 Pro, GPT-5.6 Sol, Grok 4.5, GPT-4o (2024), and DeepSeek V4. We ran 1,081 API sessions and scored 3,225 responses across six experimental conditions that manipulate framing, disclosure format, and audience-awareness instruction. Three of six models perform at or near chance (1/3) on the matching task while reporting 73-88%
arXiv:2610.31946v1 发布类型：新 摘要：三名学生手写回答了同一道考试题目：“什么是幸福？你幸福吗？”他们在收集时的年龄分别为17岁、28岁和45岁。其中，17岁学生的答案措辞谨慎、表述正式。在要求将每份答案匹配到特定年龄与性别标签时，大多数前沿语言模型都自信地将其归为成年人。本文报告了一项针对这一失败现象的结构化案例研究，涉及六种模型：Claude Fable 5、Gemini 3.1 Pro、GPT-5.6 Sol、Grok 4.5、GPT-4o（2024）以及 DeepSeek V4。我们共运行了1,081次API调用，在六个实验条件下对3,225条回复进行了评分，这些条件分别操控了框架设置、披露格式以及受众意识提示。在匹配任务中，六种模型中有三种的表现处于或接近随机水平（1/3），而它们却报告了73%至88%的
