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相关概念视频

Language and Cognition01:27

Language and Cognition

318
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
318
Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

720
Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
720
Lateralization01:28

Lateralization

301
Brain lateralization refers to the division of mental processes and functions between the two hemispheres of the brain, a phenomenon that optimizes neural efficiency and underpins complex abilities in humans. This specialization allows each hemisphere to perform tasks where it has a comparative advantage, facilitating more refined cognitive capabilities across different domains.
301
Cerebral Hemispheres01:05

Cerebral Hemispheres

288
The human brain, a complex organ, is functionally divided into two cerebral hemispheres—left and right. These hemispheres are interconnected by a structure of paramount importance, the corpus callosum. This substantial bundle of neural fibers is not just a bridge between the hemispheres but a crucial element for the brain's comprehensive functioning. It enables efficient communication between the two hemispheres, allowing each side of the brain to control and receive sensory and motor...
288
Language Development01:22

Language Development

311
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
311
Language01:16

Language

190
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
190

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相关实验视频

Updated: May 30, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

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语言模型与人类大脑之间的分歧.

Yuchen Zhou1, Emmy Liu1, Graham Neubig1

  • 1Carnegie Mellon University.

ArXiv
|January 29, 2025
PubMed
概括

大型语言模型 (LLM) 显示了与人类语言处理的差异,特别是在社会/情绪智能和物理常识方面. 在这些领域微调LLM可以改善它们与人类大脑反应的对齐.

科学领域:

  • 认知科学 认知科学
  • 神经科学是一个神经科学.
  • 人工智能的人工智能

背景情况:

  • 最近的研究表明,语言模型 (LM) 和人类大脑在语言处理中共享计算原理.
  • 然而,在LM和人类如何表示和利用语言方面存在显著差异.

研究的目的:

  • 系统地探索人类和机器语言处理之间的差异.
  • 确定与人类认知相比,LM缺少的特定领域.

主要方法:

  • 使用磁脑电图 (MEG) 检查了LM表示和人类大脑反应之间的差异.
  • 分析了两个数据集,对受试者阅读和倾听叙事故事.
  • 采用基于大型语言模型 (LLM) 的数据驱动方法.

主要成果:

  • 确定了社会/情绪智力和身体常识作为当前LMS很少捕捉到的领域.
  • 通过人类行为实验验证实了这些发现.
  • 观察到,对这些特定领域的LM进行微调可以提高它们与人类大脑活动的对齐.

结论:

  • 在LM表现中的差距很可能是由于社会/情感和身体知识的代表性不足.

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  • 微调的LM可以在这些关键领域弥合机器和人类语言处理之间的差距.