如果对这个研究分支感兴趣,我建议你继续阅读GPT-2([PDF] Language Models are Unsupervised Multitask Learners | Semantic Scholar)和GPT-3(Language Models are Few-Shot Learner)的论文。这两篇论文说明了LLMs能够进行零和Few-Shot学习,并突出了LLMs的新兴能力。GPT-3仍然是当前一代LLMs的流行基准和基础模型,例...
of Physics, Stony Brook Universitymdouglas@cmsa.fas.harvard.eduJuly 2023AbstractArtif i cial intelligence is making spectacular progress, and one of thebest examples is the development of large language models (LLMs) suchas OpenAI’s GPT series. In these lectures, written for readers with aback...
为此,我们发布了一个包含164个题目的评测集合。 生成时,如果只采样一个输出,Codex-12B的通过率为28.8%,Codex-300M的通过率为13.2%,GPT-J-6B为11.4%,GPT系列的其它所有模型通过率均为0。为了提升Codex的效果,我们用一些独立的函数对其进一步fine-tune,这就是Codex-S,它的通过率为37.7%。 考虑到人类在写代码的...
ChatGPT and Large Language Models with MATLAB ChatGPT 和 MATLAB 大型语言模型.pdf,MathWorks AUTOMOTIVE CONFERENCE 2023 MathWorks AUTOMOTIVE CONFERENCE 2023 Europe ChatGPT and Large Language Models with MATLAB Deborah Ferreira, PhD, MathWorks 0 MathWorks A
This paper provides a survey of the emerging area of Large Language Models (LLMs) for Software Engineering (SE). It also sets out open research challenges for the application of LLMs to technical problems faced by software engineers. LLMs' emergent properties bring novelty and creativity with ...
Large Language Models Are Neurosymbolic Reasoners 机构: University of Liverpool, United Kingdom; Eindhoven University of Technology, Netherlands; University of Technology Sydney, Australia; University College London, United Kingdom 论文链接: https://arxiv.org/pdf/2401.09334.pdf ...
摘要原文 It has been suggested that large language models such as GPT-4 have acquired some form of understanding beyond the correlations among the words in text including some understanding of mathematics as well. Here, we perform a critical inquiry into this claim by evaluating the mathematical ...
Large language Models (LLMs)- A Backgrounder September 2023 0|Page Large Language Models (LLMs) – A Backgrounder 1. LLMs – The Story So Far To begin with, Generative AI as a whole is powered by large and complex deep learning models pre-trained on vast amounts of dat...
自然语言提示工程(natural language prompt engineering):它为人类提供了一个自然的界面与机器沟通,这里的机器不仅限于LLMs,也包括诸如提示驱动的图像合成器之类的模型。 以上这些研究方向的背后,都隐含了一个事实: 因为LLMs本质是一个序列条件概率模型,简单的语言提示并不总是能产生预期的结果,输入序列的每一个微小地...
论文链接:https://arxiv.org/pdf/2402.06196.pdf 近期发表的比较好的一篇关于大模型的综述性文章,对大语言模型(LLMs)进行一个全面的概述、回顾与分析。文章一共包含了七个部分: 1、介绍了语言建模的历史背景,从统计语言模型到神经网络模型,再到预训练语言模型和LLMs的发展 ...