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相关概念视频

Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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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.
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Social proof is a form of persuasion based on comparison and conformity. People compare their behavior and actions to what others are doing and will change to conform to do what their peers do.
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Reasoning is the action of thinking about something in a logical, sensible way. It is integral to problem-solving, decision-making, and critical thinking. Reasoning can be inductive or deductive. Reasoning involves transforming information into conclusions, which is essential for problem-solving, decision-making, and critical thinking.
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If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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可解释的NLP的合理化:一项调查调查.

Sai Gurrapu1, Ajay Kulkarni2, Lifu Huang1

  • 1Department of Computer Science, Virginia Tech, Blacksburg, VA, United States.

Frontiers in artificial intelligence
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PubMed
概括
此摘要是机器生成的。

自然语言处理 (NLP) 中可解释的AI (人工智能) 正在推进合理化,提供人类可以理解的解释. 这项调查组织了现场,并为未来的研究引入了理性AI (RAI).

关键词:
自然语言处理自然语言处理.一个抽象的逻辑论证.可以解释的NLP.提取的理由 提取的理由大型语言模型.自然语言的生成.有理性的理由.合理化的合理化.

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科学领域:

  • 人工智能的人工智能
  • 自然语言处理自然语言处理.
  • 可解释的人工智能

背景情况:

  • 在NLP任务中深度学习的进步提高了性能,但降低了模型的可解释性.
  • 黑盒模型阻碍了对系统内部和决策过程的理解.
  • 现有的可解释性方法 (例如,LIME,Shapley,突出热图) 需要专业知识,而且不够.

研究的目的:

  • 提供2007年至2022年NLP理性化文献的第一个全面调查.
  • 在NLP合理化中组织和分析现有的方法,评估,代码和数据集.
  • 引入理性AI (RAI) 作为可解释AI的新子领域,以推进合理化.

主要方法:

  • 在自然语言处理中的合理化技术的系统文献综述.
  • 分析方法,评估指标,可用的代码和数据集.
  • 研究的分类和趋势和差距的识别.

主要成果:

  • 合理化为模型输出提供直观,人类可以理解的自然语言解释 (理性解释).
  • 在NLP的合理化领域目前是无组织的.
  • 确定了用于合理化研究的关键方法,评估策略和资源.

结论:

  • 合理化是一种可供非技术用户使用的可解释性技术.
  • 该调查为新兴的理性AI (RAI) 领域奠定了基础.
  • 讨论了NLP合理化的未来研究方向和机会.