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Language and Cognition01:27

Language and Cognition

460
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.
460
Language Development01:22

Language Development

461
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...
461
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...
1.0K
Language01:16

Language

430
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...
430
Stereotype Content Model02:16

Stereotype Content Model

14.9K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.9K
Components of Language01:24

Components of Language

413
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.
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相关实验视频

Updated: Sep 18, 2025

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
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Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

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通过多模式语言模型进行社会推理意识轨迹预测.

Inhwan Bae, Junoh Lee, Hae-Gon Jeon

    IEEE transactions on pattern analysis and machine intelligence
    |June 20, 2025
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了VLMTraj,这是一款利用大型语言模型进行增强的行人运动预测的新型多式联运轨迹预测器. 通过理解社会背景和更准确地预测未来的路径,VLMTraj的表现优于现有方法.

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    相关实验视频

    Last Updated: Sep 18, 2025

    Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
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    科学领域:

    • 计算机视觉 计算机视觉
    • 人工智能的人工智能
    • 自然语言处理自然语言处理.

    背景情况:

    • 大型语言模型 (LLM) 的进步提供了强大的上下文理解和生成能力.
    • 现有的轨迹预测方法经常与复杂的社会互动和场景背景作斗争.

    研究的目的:

    • 提出VLMTraj,一个新的多式联运轨迹预测器,利用多式联运大型语言模型的知识.
    • 将轨迹预测重新定义为视觉问题答案任务,以提高推理能力.

    主要方法:

    • VLMTraj将历史轨迹和场景图像转换为自然语言提示和视觉令牌.
    • 它使用辅助的多任务问答模块来提高对场景背景和社会关系的理解.
    • 训练包括优化数字标记器,然后在视觉问题答案提示上训练语言模型.

    主要成果:

    • 与现有的基于数值的轨迹预测器相比,VLMTraj表现出卓越的性能.
    • 该模型成功地解释了行人之间的社会关系.
    • 它准确地预测了公共基准上的多式联运未来轨迹.

    结论:

    • 基于语言的模型,如VLMTraj,对于行人轨迹预测是有效的.
    • 拟议的方法展示了利用LLM来完成复杂的时空推理任务的潜力.