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相关概念视频

Language01:16

Language

904
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...
904
Positive Symptoms Schizophrenia: Hallucinations and Delusions01:26

Positive Symptoms Schizophrenia: Hallucinations and Delusions

542
Schizophrenia is a complex psychiatric disorder characterized by a range of symptoms that significantly impact cognition, behavior, and emotional regulation. Among these, the positive symptoms stand out as they involve the addition or exaggeration of normal mental functions, deviating markedly from typical behavior and perception. Hallucinations and delusions are prominent positive symptoms, each profoundly affecting the individual's experience of reality.
Hallucinations
Hallucinations in...
542
Fineness of Cement01:15

Fineness of Cement

507
The fineness of cement directly influences the rate of hydration, as the hydration begins at the surface of the cement particles. In addition to hydration, the fineness of cement is vital for various properties of concrete including workability, gypsum requirement, and long-term behavior. The fineness of cement is represented in terms of the specific surface of cement which is typically measured in square meters per kilogram, with several methods available for this determination.
Direct...
507
Fineness Modulus01:19

Fineness Modulus

1.5K
The fineness modulus (FM) of aggregate is a numerical index that measures the coarseness or fineness of the particles. It is calculated by adding the cumulative percentages of aggregate retained on each of a specified series of sieves and dividing the sum by 100.
Consider performing sieve analysis on sand through a set of ASTM sieves. The weight of aggregate retained in each sieve and pan placed at the bottom is recorded, as given in Column B of Table 1.
To determine the fineness modulus of...
1.5K
Positive Symptoms of Schizophrenia: Hallucinations and Delusions01:30

Positive Symptoms of Schizophrenia: Hallucinations and Delusions

603
Schizophrenia is a complex mental health disorder that can manifest with various positive symptoms, including thought, movement, and behavior disorders. These symptoms significantly disrupt cognitive and motor functions, leading to profound effects on an individual's ability to engage with the world.
Thought Disorders
Disorganized and unusual thought processes mark thought disorders in schizophrenia. One key feature is disorganized speech, where an individual's conversation includes...
603
Components of Language01:24

Components of Language

809
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.
809

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相关实验视频

Updated: Jan 28, 2026

Fine-tuning the Size and Minimizing the Noise of Solid-state Nanopores
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微调大型语言模型使用实体幻觉指数进行文本总结.

Praveenkumar K1, Rakesh Chandra Balabantaray2, Kali Prasad Vittala3

  • 1Computer Science Department, International Institute of Information Technology; Global Customer Success, Informatica Business Solutions.

Journal of visualized experiments : JoVE
|January 26, 2026
PubMed
概括

本研究引入了一种新的框架,用于减少抽象总结中的幻觉,使用实体幻觉指数 (EHI) 作为奖励信号. 使用EHI微调大型语言模型 (LLM),可以提高实体忠实性和概括性.

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Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization
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Last Updated: Jan 28, 2026

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科学领域:

  • 自然语言处理自然语言处理.
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 大型语言模型 (LLM) 具有先进的抽象总结.
  • 实体级别的幻觉 (引入错误的实体) 仍然是LLM生成总结的一个关键挑战.
  • 现有的方法很难确保事实准确性和实体忠实性.

研究的目的:

  • 提出一个奖励驱动的微调框架,以减轻实体幻觉在抽象的总结.
  • 引入实体幻觉指数 (EHI) 作为指导总结模型微调的指标.
  • 增强基于LLM的总结的实际性和稳定性.

主要方法:

  • 在像XSUM.UM这样的数据集上使用预先训练的LLM (例如Flan-T5,DistilBART,Mistral) 生成初始摘要.
  • 计算了实体幻觉指数 (EHI),通过比较生成的摘要和黄金引用中的命名实体.
  • 使用强化学习作为奖励信号,使用REINFORCE风格的更新机制进行微调.

主要成果:

  • 用EHI微调的模型显示幻觉率明显较低.
  • 摘要的信息性保持不变,没有妥协.
  • 以EHI为指导的模型在域外总结任务上表现出更好的概括性,这表明了增强的稳定性.

结论:

  • 拟议的EHI引导微调框架有效地减少了实体幻觉在抽象总结.
  • 这种方法提供了一种实际的方法来提高LLM生成的摘要的实际性.
  • 准确的实体表示对于可靠的抽象总结至关重要.