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相关概念视频

Language and Cognition01:27

Language and Cognition

345
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.
345
Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

809
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...
809
Lateralization01:28

Lateralization

330
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.
330
Language01:16

Language

213
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...
213
Dissociative Disorders01:27

Dissociative Disorders

108
Dissociative disorders represent complex psychological conditions characterized by disruptions in consciousness, memory, identity, or perception. These disruptions cause individuals to experience a disconnection from their thoughts, emotions, and memories. The phenomenon is not merely an occasional lapse in attention but a profound alteration in mental functioning that can severely impact daily life.
Dissociative Fugue
A hallmark feature of dissociative disorders is the dissociative fugue...
108
Language Development01:22

Language Development

360
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...
360

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Updated: Jun 30, 2025

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在大型语言模型中分离语言和思想.

Kyle Mahowald1, Anna A Ivanova2, Idan A Blank3

  • 1The University of Texas at Austin, Austin, TX, USA.

Trends in cognitive sciences
|March 20, 2024
PubMed
概括

大型语言模型 (LLM) 显示出强大的正式语言能力,但与功能能力扎. 掌握这两种语言可能需要专门的机制来使用类似人类语言.

关键词:
认知神经科学 认知神经科学计算建模计算建模语言和思想的语言和思想.大型语言模型.语言能力 语言能力

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科学领域:

  • 人工智能的人工智能
  • 计算语言学 计算语言学
  • 认知科学 认知科学

背景情况:

  • 大型语言模型 (LLM) 接近人类语言掌握,但他们的能力仍在争论中.
  • 人类语言能力涉及不同的形式 (基于规则) 和功能 (上下文) 方面.
  • 神经科学揭示了人类正式和功能性语言能力的单独的神经支.

研究的目的:

  • 根据正式与功能性语言能力的区别来评估大型语言模型 (LLM).
  • 为了比较LLM在正式和功能任务上的表现.
  • 探索对开发类似人类的人工智能语言能力的影响.

主要方法:

  • 在对旨在探讨正规语言能力 (例如语法,语法) 的任务进行评估的课程中,对LLM进行了评估.
  • 在测量功能性语言能力 (例如,现实世界语言使用,上下文理解) 的任务上评估了LLM.
  • 与人类神经科学关于语言处理的发现相比,对表现进行了分析.

主要成果:

  • 法学士在正式语言能力方面表现出显著的熟练程度.
  • 在功能性语言能力任务上LLM的表现不一致,通常需要微调或外部模块.
  • 在法学士的基于规则的知识与他们在语境中有效使用语言的能力之间存在差距.

结论:

  • 士在掌握语言规则方面表现出色,但在功能性地应用语言方面落后,反映了人类的认知专业化.
  • 在人工智能中实现类似人类的语言能力可能需要为正式和功能能力开发不同的机制.
  • 未来的LLM发展应该集中在弥合功能性语言能力的差距,以实现更强大的语言理解和生成.