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

Light Acquisition02:16

Light Acquisition

In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
Improving Translational Accuracy02:07

Improving Translational Accuracy

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...
Improving Translational Accuracy02:07

Improving Translational Accuracy

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...

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

Quality perceptions and intended engagement in response to AI-generated and AI-assisted news.

Scientific reports·2026
Same author

Counterspeech encouraging users to adopt the perspective of minority groups reduces hate speech and its amplification on social media.

Scientific reports·2025
Same author

Existential risk narratives about AI do not distract from its immediate harms.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Comparing methods for creating a national random sample of twitter users.

Social network analysis and mining·2025
Same author

We need to understand the effect of narratives about generative AI.

Nature human behaviour·2024
Same author

People are skeptical of headlines labeled as AI-generated, even if true or human-made, because they assume full AI automation.

PNAS nexus·2024
Same journal

Anchoring race: improving the construction of race dimensions in word embeddings.

Journal of computational social science·2026
Same journal

Exploring the structure of the school curriculum with graph neural networks.

Journal of computational social science·2025
Same journal

Simulating relational event history data: why and how.

Journal of computational social science·2025
Same journal

Reducing sexual predation and victimization through warnings and awareness among high-risk users.

Journal of computational social science·2025
Same journal

Identification of intimate partner violence from free text descriptions in social media.

Journal of computational social science·2025
Same journal

Capitalizing on a crisis: a computational analysis of all five million British firms during the Covid-19 pandemic.

Journal of computational social science·2025
查看所有相关文章

相关实验视频

Updated: Jun 19, 2026

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
13:01

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

3.6K

文本注释的开源LLM:模型设置和微调的实用指南.

Meysam Alizadeh1, Maël Kubli1, Zeynab Samei2

  • 1Department of Political Science, University of Zurich, 8050 Zurich, Switzerland.

Journal of computational social science
|December 23, 2024
PubMed
概括
此摘要是机器生成的。

微调的开源大型语言模型 (LLM) 显著提高了政治学文本分类任务的性能,优于零射击模型,并为少数射击培训提供了切实可行的替代方案.

关键词:
聊天GPT 聊天 在GPT 聊天弗兰克 弗兰克在法律上,LLMs.拉拉玛拉拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛拉玛在NLP中,我们使用了NLP.这是开源的,是开源的.文字注释 文字注释

更多相关视频

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

2.4K
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

500

相关实验视频

Last Updated: Jun 19, 2026

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
13:01

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

3.6K
Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

2.4K
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

500

科学领域:

  • 政治科学 政治科学是指政治学.
  • 计算社会科学 计算社会科学
  • 自然语言处理自然语言处理.

背景情况:

  • 开源大型语言模型 (LLM) 越来越多地用于文本分析.
  • 学者需要指导LLM表现特定的政治学任务.
  • 在社会科学研究中建立LLM有效性的基准至关重要.

研究的目的:

  • 评估开源LLMs在政治学文本分类中的表现.
  • 为了比较零射击和微调的LLM能力在任务,如立场,主题和相关性.
  • 为LLM有效性提供一个基准,并为学术决策提供信息.

主要方法:

  • 使用零射击和微调方法评估开源LLM.
  • 使用新闻文章和推特数据集进行文本注释任务.
  • 与有限的注释数据相比,微调与少数射击训练进行比较.

主要成果:

  • 微调增强了开源LLM性能,与零射击GPT-3.5和GPT-4相匹配或超过.
  • 微调的开源LLM仍然落后于微调的GPT-3.5.5.
  • 微调更有效,而不是使用适度数据进行几次射击训练.

结论:

  • 精心调整的开源LLM适用于政治学中的各种文本注释应用.
  • 该研究为社会科学研究中的LLM绩效提供了实际的基准.
  • 有一个Python笔记本可用于帮助研究人员应用LLM进行文本注释.