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你只需要注意 (在大脑中):人类海马体中的语义上下文化
bioRxiv : the preprint server for biology
|July 16, 2025
概括
大脑神经元像大型语言模型 (LLM) 一样处理单词含义,通过加权总结使用上下文信息. 这一发现表明,大脑和人工智能对语言理解的计算原理相似.
科学领域:
- 神经科学是一个神经科学.
- 计算语言学 计算语言学
- 人工智能的人工智能
背景情况:
- 自然语言的理解依赖于语境中的词语含义.
- 基于变压器的大型语言模型 (LLM) 使用自我注意机制进行上下文化.
研究的目的:
- 调查大脑语言处理,特别是语境化,是否反映了LLM自我注意力机制.
- 探索人类海马体中单词位置和上下文总结的神经编码.
主要方法:
- 在听觉语言理解 (收听播客) 过程中记录了人类海马中的单个单元神经反应.
- 分析了定位编码 (序列和频率域) 的神经数据,并加权了词汇表示的总和.
- 与LLM衍生的自我注意力权重相关的神经上下文化权重.
主要成果:
- 海马神经元在多个尺度上编码句子中的单词位置,使用顺序和频率域方法.
- 对单词的神经反应反映了该词的嵌入和其语境化词语嵌入的加权总和.
- 在神经反应中对上下文信息的权重与LLM自我注意力权重相关.
- 神经上下文化与同时预测下一个单词相一致.
结论:
- 人类海马体采用类似于LLM自我注意力语言处理的原理.
- 面向预测的计算目标可能是大脑和AI语言处理中的重叠机制的基础.
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