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English(EN) Competing Influence in LLM Populations: Budget Timing and Baseline Drift

LLM代理的观点会因竞选时机和自然漂移而改变

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新的arXiv论文探讨了大型语言模型（LLM）代理在受到竞争性影响活动时，其观点如何发生变化。研究发现，竞选支出的时机以及LLM的自然演变显著影响了观察到的观点转变。在考虑了基线漂移后，竞选驱动的变化比竞选者指定的角色更接近声明的事实依据。研究还强调，LLM群体倾向于随着时间的推移失去立场多样性，并且竞选活动可以减少隔离社区之间的差异。 AI

影响 这项研究为理解LLM代理如何被影响以及它们的观点如何演变提供了见解，这可能有助于设计更健壮的AI系统和理解AI交互。

排序理由 该集群包含一篇详细介绍LLM行为研究的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.MA (Multiagent) 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

LLM代理的观点会因竞选时机和自然漂移而改变

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该集群包含一篇详细介绍LLM行为研究的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Nicolas Fay ·

    LLM群体中的竞争性影响：预算时机与基线漂移

    When competing campaigns target a population of large language model (LLM) agents, observed opinion changes may reflect both campaign influence and changes that would occur without intervention. We study how the timing of campaign expenditure and the population's own evolution sh…

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