Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Language Development01:22

Language Development

447
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...
447
Language and Cognition01:27

Language and Cognition

440
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.
440
Components of Language01:24

Components of Language

392
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.
392
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.9K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.9K
Language01:16

Language

423
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...
423
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

116
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
116

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Reflections on Visualizing the COVID-19 Pandemic for the Public.

IEEE computer graphics and applications·2026
Same author

Generating Coherent Visualization Sequences for Multivariate Data by Causal Graph Traversal.

IEEE transactions on visualization and computer graphics·2026
Same author

MisVisFix: An Interactive Dashboard for Detecting, Explaining, and Correcting Misleading Visualizations using Large Language Models.

IEEE transactions on visualization and computer graphics·2025
Same author

What is the Color of Serendipity? Investigating the Use of Language Models for Semantically Resonant Color Generation.

IEEE transactions on visualization and computer graphics·2025
Same author

Charts-of-Thought: Enhancing LLM Visualization Literacy Through Structured Data Extraction.

IEEE transactions on visualization and computer graphics·2025
Same author

Into the Void: Mapping the Unseen Gaps in High Dimensional Data.

IEEE transactions on visualization and computer graphics·2025
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026
Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026
Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026
查看所有相关文章

相关实验视频

Updated: Sep 10, 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

681

使用大型语言模型进行交互式因果模型开发和改进

Yanming Zhang, Akshith Kota, Eric Papenhausen

    IEEE transactions on visualization and computer graphics
    |August 25, 2025
    PubMed
    概括
    此摘要是机器生成的。

    这项研究介绍了CausalChat,一种使用大型语言模型 (LLM) 构建因果网络的视觉分析工具. 用户可以通过对话互动探索变量关系并识别因果结构.

    更多相关视频

    Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
    05:47

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

    Published on: June 13, 2025

    575
    Constructing and Visualizing Models using Mime-based Machine-learning Framework
    06:19

    Constructing and Visualizing Models using Mime-based Machine-learning Framework

    Published on: July 22, 2025

    634

    相关实验视频

    Last Updated: Sep 10, 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

    681
    Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
    05:47

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

    Published on: June 13, 2025

    575
    Constructing and Visualizing Models using Mime-based Machine-learning Framework
    06:19

    Constructing and Visualizing Models using Mime-based Machine-learning Framework

    Published on: July 22, 2025

    634

    科学领域:

    • 数据科学
    • 人工智能
    • 网络科学

    背景情况:

    • 因果网络对于模拟不同领域变量之间的复杂关系至关重要.
    • 现有的因果网络构建方法通常依赖于人类的专业知识,需要大量的领域知识和参与.

    研究的目的:

    • 通过利用大型语言模型 (LLM) 中嵌入的知识来构建因果网络的新方法.
    • 介绍一个视觉分析界面,用于交互式因果网络发现.
    • 用不同的数据集和用户群体评估CausalChat的有效性.

    主要方法:

    • 利用LLM (例如GPT-4) 从广泛的文献中获得的因果知识.
    • 开发了一个视觉分析界面 (CausalChat),使变量可被递归探索.
    • 将用户交互转化为定制的LLM提示,用于识别因果关系,潜在变量,混因素和调解因素.
    • 集成的视觉表示与文本解释,以提高理解.

    主要成果:

    • 在各种数据环境中展示了CausalChat的功能.
    • 涉及领域专家和非专业人士的用户研究证实了该工具的有用性.
    • 通过对话式探索,该系统成功地建立了详细的因果网络.

    结论:

    • 提供创新的因果网络构建方法,减少对广泛的人类领域专业知识的依赖.
    • 基于LLM的视觉分析为复杂的数据关系发现提供了一个有前途的途径.
    • 对于具有不同领域知识水平的用户来说,该方法具有适应性和有效性.