预设文化身份：姓名如何影响大语言模型的回应

摘要

姓名与人类身份紧密相连，它们不仅是个人独特性的标志，也承载着文化遗产与个人历史。然而，将姓名作为身份的核心标识可能导致对复杂身份的过度简化。在与大型语言模型（LLMs）互动时，用户姓名是实现个性化的重要信息点。姓名可能通过用户直接输入（由聊天机器人请求）、作为任务上下文的一部分（如简历审查）或作为内置记忆功能存储用户信息以实现个性化，进入聊天机器人对话。我们通过测量LLMs在回应常见建议寻求查询时产生的文化预设，研究了与姓名相关的偏见，这些查询可能涉及对用户的假设。我们的分析表明，在多种文化背景下，LLM生成的内容中存在着与姓名相关的强烈文化身份假设。本研究对设计更为细致的个性化系统具有启示意义，旨在避免强化刻板印象的同时，保持有意义的定制化。

English

Names are deeply tied to human identity. They can serve as markers of individuality, cultural heritage, and personal history. However, using names as a core indicator of identity can lead to over-simplification of complex identities. When interacting with LLMs, user names are an important point of information for personalisation. Names can enter chatbot conversations through direct user input (requested by chatbots), as part of task contexts such as CV reviews, or as built-in memory features that store user information for personalisation. We study biases associated with names by measuring cultural presumptions in the responses generated by LLMs when presented with common suggestion-seeking queries, which might involve making assumptions about the user. Our analyses demonstrate strong assumptions about cultural identity associated with names present in LLM generations across multiple cultures. Our work has implications for designing more nuanced personalisation systems that avoid reinforcing stereotypes while maintaining meaningful customisation.

预设文化身份：姓名如何影响大语言模型的回应

Presumed Cultural Identity: How Names Shape LLM Responses

摘要

Summary

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