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相关概念视频

Language Development01:22

Language Development

841
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...
841
Language and Cognition01:27

Language and Cognition

704
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.
704
Stereotype Content Model02:16

Stereotype Content Model

15.3K
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...
15.3K
Language01:16

Language

878
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...
878
Observational Learning01:12

Observational Learning

824
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
824
Associative Learning01:27

Associative Learning

1.2K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
1.2K

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相关实验视频

Updated: Jan 14, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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使用Pepper探索多式联动讲故事:一项初步研究,使用零射击的LLM.

Unai Zabala1, Juan Echevarria1, Igor Rodriguez1

  • 1Department of Computer Science and Artificial Intelligence, University of the Basque Country (EHU), Donostia, Spain.

Frontiers in robotics and AI
|October 24, 2025
PubMed
概括

本研究探讨了使用大型语言模型 (LLM) 的社交机器人进行协作讲故事. 这种新的系统整合了物理物体和富有表现力的机器人表演,显示了用户对交互式叙事的高度接受.

科学领域:

  • 人与机器人的交互
  • 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) 在虚拟代理中越来越多地用于协作讲故事.
  • 在讲故事的社会机器人中,LLM的整合仍然未被充分探索.
  • 讲故事是社交机器人吸引观众的传统方法.

研究的目的:

  • 介绍一款新型多式联运合作讲故事系统的初步步骤.
  • 调查LLM用于自主故事生成和适应的使用.
  • 评估LLM在社交机器人交互式讲故事中的可用性和成熟度.

主要方法:

  • 开发了一个多式联络系统,用户可以与社交机器人Pepper共同创建故事.
  • 利用基于YOLO的视觉系统进行对象识别和叙事集成.
  • 采用拉玛模型进行零拍摄故事生成和改编.
  • 通过机器人的表达性手势,情感线索和语音调制来增强沉浸感.

主要成果:

  • 该系统成功地将用户提供的物理对象集成到叙事中.
  • 拉玛模型在零拍摄环境中自主生成和调整故事.
  • 社交机器人Pepper通过表达性的非语言和语言线索来执行故事.
关键词:
合作式的讲故事方式这就是手势生成.人与机器人的交互社会机器人社会机器人一个零射击的LLM.

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  • 用户反表明,合作讲故事系统的接受程度很高.
  • 结论:

    • 在人机交互中,LLM显示出自主故事生成的前景.
    • 多模式输入,包括物理对象,增强了协作式讲故事体验.
    • 表达式的机器人表演对于增加沉浸和用户接受交互式叙述至关重要.