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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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Related Experiment Video

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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Social Reasoning-Aware Trajectory Prediction via Multimodal Language Model.

Inhwan Bae, Junoh Lee, Hae-Gon Jeon

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |June 20, 2025
    PubMed
    Summary

    This study introduces VLMTraj, a novel multimodal trajectory predictor leveraging large language models for enhanced pedestrian movement forecasting. VLMTraj outperforms existing methods by understanding social context and predicting future paths more accurately.

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    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Natural Language Processing

    Background:

    • Advancements in large language models (LLMs) offer powerful context understanding and generative capabilities.
    • Existing trajectory prediction methods often struggle with complex social interactions and scene context.

    Purpose of the Study:

    • To propose VLMTraj, a novel multimodal trajectory predictor that utilizes the knowledge from multimodal large language models.
    • To reframe trajectory prediction as a visual question answering task for enhanced reasoning.

    Main Methods:

    • VLMTraj converts historical trajectories and scene images into natural language prompts and visual tokens.
    • It employs an auxiliary multi-task question-answering module to improve understanding of scene context and social relationships.
    • Training involves optimizing a numerical tokenizer and then training the language model on visual question answering prompts.

    Main Results:

    • VLMTraj demonstrates superior performance compared to existing numerical-based trajectory predictors.
    • The model successfully interprets social relationships between pedestrians.
    • It accurately predicts multimodal future trajectories on public benchmarks.

    Conclusions:

    • Language-based models, like VLMTraj, are effective for pedestrian trajectory prediction.
    • The proposed method showcases the potential of leveraging LLMs for complex spatiotemporal reasoning tasks.