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相关概念视频

Language Development01:22

Language Development

444
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...
444
Language and Cognition01:27

Language and Cognition

438
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.
438
Language01:16

Language

422
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...
422
Components of Language01:24

Components of Language

388
Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
388
Modeling and Similitude01:12

Modeling and Similitude

328
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
328
Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

1.0K
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...
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相关实验视频

Updated: Sep 9, 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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大型语言模型可以模拟人类的对话吗?

Eric Mayor1, Lucas M Bietti2, Adrian Bangerter3

  • 1Department of Psychology, University of Basel.

Cognitive science
|September 1, 2025
PubMed
概括
此摘要是机器生成的。

大型语言模型 (LLM) 与人类电话对话相比显示过度对齐和不适当使用对话标记. 目前的LLM并不总是有效地模拟人类的口语对话.

关键词:
计算方法对话协调法学士与法学士的对话语言对齐通过口语进行对话

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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相关实验视频

Last Updated: Sep 9, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Published on: December 6, 2024

681
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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科学领域:

  • 计算语言学
  • 人工智能
  • 人与计算机的互动

背景情况:

  • 大型语言模型 (LLM) 在模拟人类认知方面表现出先进的能力,特别是在基于聊天的交互中.
  • 尽管LLM作为一种范式转变的潜力,但其模拟人类口语对话的能力仍然在很大程度上未被探索.

研究的目的:

  • 调查大型语言模型 (LLM) 可以准确模拟人类口语对话的程度.
  • 将LLM产生的对话与人类电话对话的语言特征进行比较.

主要方法:

  • 研究1:使用定制提示,将SB语录 (人类电话对话) 与LLM (GPT-4,Claude Sonnet 3.5,Vicuna,Wayfarer) 所生成的语录进行比较.
  • 分析的重点是对齐 (概念,语法,词汇),协调标记,和对话的开放/关闭.
  • 研究2:评估人类区分LLM生成的转录与人类的SB转录的能力.

主要成果:

  • 与人类对话不同的是, 随着对话的进展, LLM 会话表现出夸张的对齐.
  • 学生们表现出不同且往往不合适的协调标记和不相似的对话开头和结束.
  • 人类评估者可以从人类对话中区分LLM生成的成绩单,这表明LLM并不总是通过人类对话.

结论:

  • 目前的LLM产生的口头对话在质量和数量上与人类对话不同.
  • 差异可能源于口语对话和聊天之间的内在区别,或LLM培训和能力的局限性.
  • 未来的LLM和培训数据可能会改善模拟,但基本差异可能仍然存在.