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

Effects of feedback01:24

Effects of feedback

496
Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
496
Load-frequency control01:28

Load-frequency control

106
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
106
Reinforcement01:23

Reinforcement

169
Positive and negative reinforcement are key concepts in operant conditioning, a learning process where the consequences of a behavior affect the likelihood of that behavior being repeated.
Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
169
Feedback control systems01:26

Feedback control systems

262
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
262
Confirmation Biases01:31

Confirmation Biases

5.4K
The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
5.4K
Law of Effect01:06

Law of Effect

1.3K
B.F. Skinner, a prominent figure in behavioral psychology, introduced operant conditioning by emphasizing the role of consequences in shaping behavior. This theory builds upon the law of effect proposed by Edward Thorndike, which posits that behaviors followed by satisfying outcomes are likely to be repeated. In contrast, those followed by unsatisfying outcomes are less likely to recur.
Edward Thorndike's foundational work involved studying learning in animals, particularly using puzzle...
1.3K

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

Network and Factor Structure of Depression and Anxiety Symptoms in Telemental Healthcare Patients From Bangladesh: Evidence for Precision Mental Healthcare.

Depression and anxiety·2026
Same author

Draft genome sequence of <i>Pseudomonas aeruginosa</i> SAU_MI_1F1 isolated from feces of cattle in Dhaka, Bangladesh.

Microbiology resource announcements·2026
Same author

Integrated in silico and in vitro assessment of Azadirachta indica leaf extract against multi-drug resistant Citrobacter koseri and Staphylococcus saprophyticus.

Scientific reports·2026
Same author

Early feasibility of telemedicine-based mental health wellbeing centers: an implementation study in district and sub-district health facilities in Bangladesh.

BMC health services research·2026
Same author

Tele-mental health for frail older adults in rural Bangladesh: a phenomenological study.

BMC psychology·2026
Same author

Draft genome sequence of <i>Salmonella enterica</i> subsp. <i>enterica</i> serovar Typhimurium SBI_US10_MRI_BD isolated from broiler chicken in Bangladesh.

Microbiology resource announcements·2026
Same journal

Turbulent flow in a vortex separator with a directed pipe inlet.

Scientific reports·2026
Same journal

Systematic characteristic evaluation of clay-based cementitious material derived from calcium carbide residue and waste tile powder.

Scientific reports·2026
Same journal

Retraction Note: Improvement of a rapid diagnostic application of monoclonal antibodies against avian influenza H7 subtype virus using Europium nanoparticles.

Scientific reports·2026
Same journal

Applying large language models to spam detection in the Kazakh low-resource language setting.

Scientific reports·2026
Same journal

An open-source 3D printing system enabling in-situ freeze-thaw processing of hydrogels.

Scientific reports·2026
Same journal

An enhanced EfficientNet framework for automated waste classification using cosine annealing and label smoothing.

Scientific reports·2026
查看所有相关文章

相关实验视频

Updated: May 21, 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

474

在LLM培训中使用基于共识的奖励来缓解恶意RLHF反的框架.

Zafaryab Haider1, Md Hafizur Rahman2, Vijay Devabhaktuni3

  • 1Department of Electrical and Computer Engineering (ECE), University of Maine, Orono, ME, USA. zafaryab.haider@maine.edu.

Scientific reports
|March 18, 2025
PubMed
概括
此摘要是机器生成的。

一个名为COBRA的新框架解决了使用人类反 (RLHF) 强化学习训练大型语言模型 (LLM) 的安全风险. 科布拉有效地过出恶意的人类反,提高了LLM在现实应用中的性能和安全性.

关键词:
通过人类反来进行强化学习.确保人工智能的安全.值得信赖的大型语言模型

更多相关视频

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

4.9K
A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
07:05

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Published on: August 24, 2017

10.9K

相关实验视频

Last Updated: May 21, 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

474
WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

4.9K
A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
07:05

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Published on: August 24, 2017

10.9K

科学领域:

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

背景情况:

  • 大型语言模型 (LLM) 在各个行业越来越多地被采用,但面临着安全和隐私方面的挑战.
  • 强化学习从人类反 (RLHF) 对于LLM培训至关重要,传授人类的品质.
  • RLHF过程容易受到恶意反的影响,可能会降低LLM的性能并导致有害的输出.

研究的目的:

  • 提出一个新的框架,COBRA (基于共识的奖励),以减轻RLHF的恶意反.
  • 在混合信任环境中增强LLM培训性能和稳定性.
  • 为了验证COBRA对最先进的方法的有效性.

主要方法:

  • 开发了COBRA框架,这是一个基于共识的技术,用于在RLHF期间过噪音的人类反.
  • 通过使用各种LLM模型 (例如,GPT-2 XL) 评估了COBRA对情绪分析和对话任务的用例.
  • 将COBRA的性能与标准RLHF和先前的方法进行比较 (Coste等. ) 的情况.

主要成果:

  • COBRA显著提高了LLM的性能,通过[公式:查看文本]进行对话任务和[公式:查看文本]进行情绪分析来优于不受保护的奖励生成.
  • 量化比较显示,COBRA实现了最先进的性能,特别是使用更少的奖励模型.
  • 在较少的奖励模型中,COBRA证明了奖励准确度的提高 ([公式:见文本]).

结论:

  • COBRA有效地中和了RLHF中的恶意反,提高了LLM培训结果.
  • 拟议的框架为在关键应用中安全可靠的LLM开发提供了强大的解决方案.
  • 科巴在确保法学士培训数据的完整性和质量方面取得了重大进展.