检索结果-南通市图书馆

DeBERTa-GRU: Sentiment Analysis for large language model

Computers, Materials & Continua 2024年第6期79卷 4219-4236页

作者： Adel Assiri Abdu Gumaei Faisal Mehmood Touqeer Abbas Sami Ullah Department of Informatics for Business College of BusinessKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China Department of Computer Science and Technology Beijing University of Chemical TechnologyBeijing100029China Department of Computer Science Government College University FaisalabadFaisalabadPunjab38000Pakistan

Modern technological advancements have made social media an essential component of daily *** media allow individuals to share thoughts,emotions,and *** analysis plays the function of evaluating whether the sentiment of the text is positive,negative,neutral,or any other personal emotion to understand the sentiment context of the *** analysis is essential in business and society because it impacts strategic *** analysis involves challenges due to lexical variation,an unlabeled dataset,and text distance *** execution time increases due to the sequential processing of the sequence ***,the calculation times for the Transformer models are reduced because of the parallel *** study uses a hybrid deep learning strategy to combine the strengths of the Transformer and Sequence models while ignoring their *** particular,the proposed model integrates the Decoding-enhanced with Bidirectional Encoder Representations from Transformers(BERT)attention(DeBERTa)and the Gated Recurrent Unit(GRU)for sentiment *** the Decoding-enhanced BERT technique,the words are mapped into a compact,semantic word embedding space,and the Gated Recurrent Unit model can capture the distance contextual semantics *** proposed hybrid model achieves F1-scores of 97%on the Twitter large language model(LLM)dataset,which is much higher than the performance of new techniques.

关键词： DeBERTa GRU Naive Bayes LSTM sentiment analysis large language model

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Evaluating the role of large language models in inflammatory bowel disease patient information

引用

World Journal of Gastroenterology 2024年第29期30卷 3538-3540页

作者： Eun Jeong Gong Chang Seok Bang Department of Internal Medicine Hallym University College of MedicineChuncheon 24253Gangwon-doSouth Korea

This letter evaluates the article by Gravina et al on ChatGPT’s potential in providing medical information for inflammatory bowel disease *** promising,it highlights the need for advanced techniques like reasoning+action and retrieval-augmented generation to improve accuracy and *** that simple question and answer testing is insufficient,it calls for more nuanced evaluation methods to truly gauge large language models’capabilities in clinical applications.

关键词： Crohn’s disease Ulcerative colitis Inflammatory bowel disease Chat generative pre-trained transformer large language model Artificial intelligence

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Harnessing AI-human synergy for deep learning research analysis in ophthalmology with large language models assisting humans

引用

Eye Science 2024年第1期1卷 7-25页

作者：罗明杰张玮星张哲铭庞健宇林桢哲赵兰琴林铎儒林浩添 State Key Laboratory of Ophthalmology Zhongshan Ophthalmic CenterSun Yat-sen UniversityGuangdong Provincial Key Laboratory of Ophthalmology and Visual ScienceGuangdong Provincial Clinical Research Center for Ocular DiseasesGuangzhou 510060China Center for Precision Medicine and Department of Genetics and Biomedical Informatics Zhongshan School of MedicineSun Yat-sen UniversityGuangzhou 510060China Hainan Eye Hospital and Key Laboratory of Ophthalmology Zhongshan Ophthalmic CenterSun Yat-sen UniversityHaikou 570311China

Background:Research innovations inocular disease screening,diagnosis,and management have been boosted by deep learning(DL)in the last *** assess historical research trends and current advances,we conducted an artificial intelligence(AI)-human hybrid analysis of publications on DL in ***:All DL-related articles in ophthalmology,which were published between 2012 and 2022 from Web of Science,were included.500 high-impact articles annotated with key research information were used to fine-tune a large language models(LLM)for reviewing medical literature and extracting *** verifying the LLM's accuracy in extracting diseases and imaging modalities,we analyzed trend of DL in ophthalmology with 2535 ***:Researchers using LLM for literature analysis were 70%(P=0.0001)faster than those who did not,while achieving comparable accuracy(97%versus 98%,P=0.7681).The field of DL in ophthalmology has grown 116%annually,paralleling trends of the broader DL *** publications focused mainly on diabetic retinopathy(P=0.0003),glaucoma(P=0.0011),and age-related macular diseases(P=0.0001)using retinal fundus photographs(FP,P=0.0015)and optical coherence tomography(OCT,P=0.0001).DL studies utilizing multimodal images have been growing,with FP and OCT combined being the most *** the 500 high-impact articles,laboratory studies constituted the majority at 65.3%.Notably,a discernible decline in model accuracy was observed when categorizing by study design,notwithstanding its statistical ***,43 publicly available ocular image datasets were ***:This study has characterized the landscape of publications on DL in ophthalmology,by identifying the trends and breakthroughs among research topics and the fast-growing *** study provides an efficient framework for combined AI-human analysis to comprehensively assess the current status and future trends in the field.

关键词： large language model AI-human collaboration research trends ophthalmology model performance

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Four development stages of collective intelligence

引用

Frontiers of Information Technology & Electronic Engineering 2024年第7期25卷 903-916页

作者： Renbin XIAO School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

The new generation of artificial intelligence(AI)research initiated by Chinese scholars conforms to the needs of a new information environment changes,and strives to advance traditional artificial intelligence(AI 1.0)to a new stage of AI *** one of the important components of AI,collective intelligence(CI 1.0),i.e.,swarm intelligence,is developing to the stage of CI 2.0(crowd intelligence).Through in-depth analysis and informative argumentation,it is found that an incompatibility exists between CI 1.0 and CI ***,CI 1.5 is introduced to build a bridge between the above two stages,which is based on biocollaborative behavioral *** 1.5 is the transition from CI 1.0 to CI 2.0,which contributes to the compatibility of the two ***,a new interpretation of the meta-synthesis of wisdom proposed by Qian Xuesen is *** meta-synthesis of wisdom,as an improvement of crowd intelligence,is an advanced stage of bionic intelligence,i.e.,CI *** is pointed out that the dual-wheel drive of large language models and big data with deep uncertainty is an evolutionary path from CI 2.0 to CI 3.0,and some elaboration is *** a result,we propose four development stages(CI 1.0,CI 1.5,CI 2.0,and CI 3.0),which form a complete framework for the development of *** different stages are progressively improved and have good *** to the dominant role of cooperation in the development stages of CI,three types of cooperation in CI are discussed:indirect regulatory cooperation in lower organisms,direct communicative cooperation in higher organisms,and shared intention based collaboration in *** division is the main form of achieving cooperation and,for this reason,this paper investigates the relationship between the complexity of behavior and types of labor ***,based on the overall understanding of the four development stages of CI,the future development direction and research issues of CI are explored.

关键词： Collective intelligence Meta-synthesis of wisdom Incompatibility Labor division Cooperative behavior Collective intelligence emergence large language model

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

BioTreasury:a community-based repository enabling indexing and rating of bioinformatics tools

引用

Science China(Life Sciences) 2024年第2期67卷 221-229页

作者： Qi Zhao Xin Zhou Jingxing Wu Jieyi Cai Xiaoqiong Bao Lin Tang Chaoye Wang Chunlei Liu Yukai Wang Yuyan Teng Mohan Zheng Weiping Mu Zhixiang Zuo Yubin Xie Xiaotong Luo Jian Ren School of Life Sciences State Key Laboratory of Oncology in South ChinaCancer CenterGuangdong Provincial Clinical Research Center for CancerSun Yat-sen UniversityGuangzhou 510060China Institute of Precision Medicine The First Affiliated HospitalSun Yat-sen UniversityGuangzhou 510080China Guangdong Institute of Gastroenterology Department of General SurgeryGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseasesThe Sixth Affiliated HospitalSun Yat-sen UniversityGuangzhou 510275China

The exponential growth of bioinformatics tools in recent years has posed challenges for scientists in selecting the most suitable one for their data analysis ***,to aid scientists in making informed choices,a community-based platform that indexes and rates bioinformatics tools is urgently *** this study,we introduce Bio Treasury(http://***),an integrated communitybased repository that provides an interactive platform for users and developers to share their experiences in various bioinformatics *** Treasury offers a comprehensive collection of well-indexed bioinformatics software,tools,and databases,totaling over 10,000 *** the past two years,we have continuously improved and maintained Bio Treasury,adding several exciting features,including creating structured homepages for every tool and user,a hierarchical category of bioinformatics tools and classifying tools using large language model(LLM).Bio Treasury streamlines the tool submission process with intelligent ***,Bio Treasury provides a wide range of social features,for example,enabling users to participate in interactive discussions,rate tools,build and share tool collections for the *** believe Bio Treasury can be a valuable resource and knowledge-sharing platform for the biomedical *** empowers researchers to effectively discover and evaluate bioinformatics tools,fostering collaboration and advancing bioinformatics research.

关键词： bioinformatics tools index tool database rating system large language model tool collections shari

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

May ChatGPT be a tool producing medical information for common inflammatory bowel disease patients’questions?An evidencecontrolled analysis

引用

World Journal of Gastroenterology 2024年第1期30卷 17-33页

作者： Antonietta Gerarda Gravina Raffaele Pellegrino Marina Cipullo Giovanna Palladino Giuseppe Imperio Andrea Ventura Salvatore Auletta Paola Ciamarra Alessandro Federico Division of Hepatogastroenterology Department of Precision MedicineUniversity of Campania Luigi VanvitelliNaples 80138Italy

Artificial intelligence is increasingly entering everyday *** language model(LLM)systems such as Chat Generative Pre-trained Transformer(ChatGPT)have become potentially accessible to everyone,including patients with inflammatory bowel diseases(IBD).However,significant ethical issues and pitfalls exist in innovative LLM *** hype generated by such systems may lead to unweighted patient trust in these ***,it is necessary to understand whether LLMs(trendy ones,such as ChatGPT)can produce plausible medical information(MI)for *** review examined ChatGPT’s potential to provide MI regarding questions commonly addressed by patients with IBD to their *** the review of the outputs provided by ChatGPT,this tool showed some attractive potential while having significant limitations in updating and detailing information and providing inaccurate information in some *** studies and refinement of the ChatGPT,possibly aligning the outputs with the leading medical evidence provided by reliable databases,are needed.

关键词： Crohn’s disease Ulcerative colitis Inflammatory bowel disease Chat Generative Pre-trained Transformer large language model Artificial intelligence

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

图书情报领域大模型的应用模式和数据治理

引用

图书馆学情报学 2024年第5期

作者：刘倩倩刘圣婴刘炜

本文探讨了图书情报领域大语言模型的应用开发与数据治理要求。大语言模型是依赖海量文本数据，经过无监督预训练及有监督标注数据微调而成。领域大模型则是通用大模型经过领域数据的微调而得到，具备解决领域问题的能力，满足领域应用... 详细信息

本文探讨了图书情报领域大语言模型的应用开发与数据治理要求。大语言模型是依赖海量文本数据，经过无监督预训练及有监督标注数据微调而成。领域大模型则是通用大模型经过领域数据的微调而得到，具备解决领域问题的能力，满足领域应用需求。本文首先回顾了生成式人工智能的突破历程，介绍了大模型的基本原理和应用现状，分析了大模型所具备的多任务能力背后的数据因素和数据需求。最后从数据治理角度重点讨论了领域大模型的应用潜力和方法流程。本文的主要贡献在于分析了图书情报领域大模型的应用模式和数据治理，为图书馆行业应用生成式人工智能技术提供了理论依据和实践指导。同时，文章也讨论了行业大模型应用和评估时需要关注的问题和局限性。

关键词：大语言模型领域大模型大模型应用开发数据治理指令微调图书情报 large language model Domain-specific large model LLM application development Data governance Instruction fine tuning Library and information science

来源：人大复印报刊资料评论

在线全文

人大复印报刊资料

学校读者我要写书评

暂无评论

Unlearning Descartes:Sentient AI is a Political Problem

引用

Journal of Social Computing 2023年第3期4卷 193-204页

作者： Gordon Hull the School of Data Science UNC CharlotteCharlotteNC 28223USA

The emergence of large language models(LLMs)has renewed debate about whether Artificial Intelligence(AI)can be conscious or *** paper identifies two approaches to the topic and argues:(1)A“Cartesian”approach treats consciousness,sentience,and personhood as very similar terms,and treats language use as evidence that an entity is *** approach,which has been dominant in AI research,is primarily interested in what consciousness is,and whether an entity possesses it.(2)An alternative“Hobbesian”approach treats consciousness as a sociopolitical issue and is concerned with what the implications are for labeling something sentient or *** both enables a political disambiguation of language,consciousness,and personhood and allows regulation to proceed in the face of intractable problems in deciding if something“really is”sentient.(3)AI systems should not be treated as conscious,for at least two reasons:(a)treating the system as an origin point tends to mask competing interests in creating it,at the expense of the most vulnerable people involved;and(b)it will tend to hinder efforts at holding someone accountable for the behavior of the systems.A major objective of this paper is accordingly to encourage a shift in *** place of the Cartesian question-is AI sentient?-I propose that we confront the more Hobbesian one:Does it make sense to regulate developments in which AI systems behave as if they were sentient?

关键词： artificial intelligence large language model consciousness sentience personhood Descartes Hobbes

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

数智赋能信息资源管理新路径：指令工程的概念、内涵和发展

引用

图书馆学情报学 2024年第6期

作者：陆伟汪磊程齐凯刘家伟黄永

新一轮科技革命和产业变革方兴未艾，大数据、人工智能等系列数智技术对信息资源管理学科产生了深远影响。在大模型背景下，指令工程通过高质量、体系化、流程化的指令设计引导模型生成结果，是高效发挥大模型能力的重要途径，可以用于... 详细信息

新一轮科技革命和产业变革方兴未艾，大数据、人工智能等系列数智技术对信息资源管理学科产生了深远影响。在大模型背景下，指令工程通过高质量、体系化、流程化的指令设计引导模型生成结果，是高效发挥大模型能力的重要途径，可以用于解决学科相关重要问题。本文首先介绍了指令工程的概念，然后详细梳理了指令的构成要素、设计模式以及指令工程的特点和意义，并探讨了指令工程赋能信息资源管理的建设路径。未来，指令工程的研究和发展还需要关注通用及领域指令工程建设、指令工程标准化、知识产权保护、安全性和体系化测试评估等问题，以期能够在各行业复杂的应用场景中更好地发挥指令的效能。

关键词：指令工程大模型信息资源管理数智赋能 Instruction engineering large language model Information resources management Data intelligence empowerment

来源：人大复印报刊资料评论

在线全文

人大复印报刊资料

学校读者我要写书评

暂无评论

应用场景、风险与前景：ChatGPT类大语言模型时代的学术出版

引用

出版业 2024年第1期

作者：宋时磊杨逸云

以ChatGPT为标志，人工智能进入大语言模型发展阶段，其出色的理解、思维和表达能力给学术出版带来新问题、新挑战与新契机。在学术出版中，当前阶段的大语言模型工具从四个方面改变了出版生态，增强了剽窃的隐蔽性，导致知识谬误和偏... 详细信息

以ChatGPT为标志，人工智能进入大语言模型发展阶段，其出色的理解、思维和表达能力给学术出版带来新问题、新挑战与新契机。在学术出版中，当前阶段的大语言模型工具从四个方面改变了出版生态，增强了剽窃的隐蔽性，导致知识谬误和偏见的不当传播，加剧了知识产权认定的难度，引发了公平性和出版壁垒等问题。国内外的出版机构已制定了相对保守和稳妥的内容政策，初步应对和回答这些挑战和问题。在人工智能的大语言模型发展时代，科研和学术的生产和创新将会迎来生产力的大飞跃，出版业等各方应以善治理念，制定“良法”，引导、规范和促进知识生产，迎接“思维革命”时代的到来。

关键词： ChatGPT 人工智能大语言模型知识生产出版业聊天机器人 ChatGPT Artificial intelligence large language model Knowledge production Publishing industry Chatbot

来源：人大复印报刊资料评论

在线全文

人大复印报刊资料

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：