Pretrained model是指通过大量的数据训练出的大模型,可以直接或者fine tune后用在新的任务上(如果不是大模型,用少量数据训练的小模型能直接用在新的任务上也可以,但是一般来说少量数据没有强大的迁移能力,所以一般都是指大模型)。我把pretained model分为三类:图像大模型,语言大模型(LLM),Meta learning(一般指few-...
上图中是具有知识反省的 LLM 的零样本结果。之前的工作已经证明 LLM 已经捕获了大量的常识性知识,并在常识性推理任务中表现出强大的性能。在这里,我们希望调查大型语言模型是否可以从知识反思中受益。由于 LLM 对训练的计算要求很高,因此在本实验中,我们评估了零样本设置中的性能。在实施知识反省时,提示包括一条指令...
PLLM-CS: Pre-trained Large Language Model (LLM)for Cyber Threat Detection in Satellite NetworksMohammed Hassanin a , Marwa Keshk b , Sara Salim b , Majid Alsubaie c ,Dharmendra Sharma ca the University of South Australia (UniSA), SA, Australiab University of New South Wales, Canberra, ...
The official GitHub page for the survey paper "A Survey of Large Language Models". natural-language-processingpre-trainingpre-trained-language-modelsin-context-learninglarge-language-modelsllmllmschain-of-thoughtchatgptrlhfinstruction-tuning UpdatedAug 20, 2024 ...
Learning/acquiring symbolic domain models 利用LLM蕴含的大量知识,将LLM建立为world model或者一个plan critic;但是有证据显示这种model缺乏可靠的(对action effects的)reasoning,在候选的plan中容易发生错误 Language models with access to external tools 例如让LLM调用外部的数学或者逻辑归因的工具,这里作者是调用了外部...
几篇论文实现代码:《HyPe: Better Pre-trained Language Model Fine-tuning with Hidden Representation Perturbation》(ACL 2023) GitHub: github.com/Yuanhy1997/HyPe [fig7] 《Fully Attentional Networks w...
Software Testing With Large Language Models: Survey, Landscape, and Vision Pre-trained large language models (LLMs) have recently emerged as a breakthrough technology in natural language processing and artificial intelligence, wit... WangJunjie,HuangYuchao,ChenChunyang,... - 《IEEE Transactions on ...
【LLM系列之GPT】GPT(Generative Pre-trained Transformer)生成式预训练模型,GPT(GenerativePre-trainedTransformer)是由OpenAI公司开发的一系列自然语言处理模型,采用多层Transformer结构来预测下一个单词的概率分布,通过在大型文本语料库中学习到的语言模式来生成
Here we present SkinGPT-4, which is an interactive dermatology diagnostic system based on multimodal large language models. We have aligned a pre-trained vision transformer with an LLM named Llama-2-13b-chat by collecting an extensive collection of skin disease images (comprising 52,929 publicly ...
A pre-trained model may not be 100% accurate in your application, but it saves huge efforts required to re-invent the wheel. Let me show this to you with a recent example. Why would we use Pre-trained Models? I spent my last week working on a problem atCrowdAnalytix platform– Identify...