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相关概念视频

Language Development01:22

Language Development

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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...
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Introduction to Learning01:18

Introduction to Learning

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Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
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Avoidance Learning and Learned Helplessness01:14

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Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
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Generalization, Discrimination, and Extinction01:24

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Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
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Observational Learning

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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...
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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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DP2Unlearning:为LLMs提供一个高效和保证的学习框架.

Tamim Al Mahmud1, Najeeb Jebreel1, Josep Domingo-Ferrer1

  • 1Universitat Rovira i Virgili, Department of Computer Engineering and Mathematics, CYBERCAT-Center for Cybersecurity Research of Catalonia, Av. Països Catalans 26, 43007, Tarragona Catalonia.

Neural networks : the official journal of the International Neural Network Society
|July 24, 2025
PubMed
概括
此摘要是机器生成的。

大型语言模型 (LLM) 现在可以使用DP2Unlearning有效地忘记数据,这是一个提供正式保证的新框架. 这种方法确保了数据隐私和模型实用性,成本低于再培训.

关键词:
大约取消学习.不同的隐私差异性隐私.准确的忘记学习.在法学士课程中,我们要忘记学习.维护隐私的LLM法学士学位

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科学领域:

  • 人工智能的人工智能
  • 机器学习 机器学习
  • 数据 隐私 数据 隐私 数据

背景情况:

  • 大型语言模型 (LLM) 在语言任务中表现出色,但在记住私人或受版权保护的数据方面引发了伦理问题.
  • 重新训练LLM以删除特定数据是有效的,但在计算上是不可避免的.
  • 现有的近似的忘记方法缺乏正式的忘记保证.

研究的目的:

  • 介绍DP2Unlearning,这是一个新的框架,用于有效的LLM忘记,并提供正式的忘记保证.
  • 与完全再培训相比,提供一个具有成本效益的解决方案来从LLM中删除敏感信息.
  • 在保持模型性能的同时,确保对数据披露的隐私.

主要方法:

  • 培训LLM在以epsilon差异隐私 (DP) 保护的文本数据上.
  • 使用DP受保护的模型,以实现高效的忘记,并提供正式的隐私保证.
  • 将DP2Unlearning与精确的再培训和近似的学习方法进行比较.

主要成果:

  • DP2Unlearning实现的模型性能与正确的unlearning (从零开始重新培训) 后的unlearning相提并论.
  • 拟议的方法提供了大约一半的再培训计算成本的脱学.
  • 在保持模型实用性和有效地忘记目标数据方面,DP2Unlearning的表现优于近似的unlearning方法.

结论:

  • DP2Unlearning提供了一种实用和理论上合理的方法来解决LLM的学习问题.
  • 该框架平衡了数据隐私,模型实用性和计算效率.
  • 这种方法为解决LLM部署中的伦理和法律挑战提供了可行的解决方案.