随着大语言模型(LLM)的参数规模增长到数千亿,并开始显示出早期的通用人工智能迹象,它们的应用也已经超越了文本处理。Codex首创将LLM应用于代码处理,取得了令人惊叹的结果,催生了GitHub Copilot等商业产品和StarCoder、Code LLaMA等数十亿参数的开源代码模型。 然而,将预训练Transformer应用于代码处理可以追溯到自回归模型成...
Going into their applications across diverse domains such as natural language processing, machine translation, sentiment analysis, chatbots, and text generation, this review elucidates the profound impact of LLMs on various industries and societal aspects. Furthermore, it explores the multifaceted future...
论文链接:A Survey on Evaluation of Large Language Models 大模型综述 介绍 关注三个关键问题:要评估什么,在哪里要评估,以及如何评估 人们普遍认为,真实的智力使我们具备推理能力,使我们能够测试假设,并为未来的现实发展做好准备。 评价LLM的重要性 评价LLM帮助我们更好地了解LLM的优点和缺点 更好的评估可以为人类...
a survey on evaluation of llmsa survey on evaluation of llms中文翻译 a survey on evaluation of llms翻译成中文意思为:远程学习管理系统评价研究综述。©2022 Baidu |由 百度智能云 提供计算服务 | 使用百度前必读 | 文库协议 | 网站地图 | 百度营销 ...
To the best of our knowledge, our survey is the first to cover all three key aspects related to security and privacy for the first time. Second, we have made several interesting discoveries. For instance, our research reveals that LLMs contribute more positively than negatively to security and...
A survey on LLM-based multi-agent systems: workflow, infrastructure, and challenges 来自 Springer 喜欢 0 阅读量: 14 作者:X Li,S Wang,S Zeng,Y Wu,Y Yang 摘要: The pursuit of more intelligent and credible autonomous systems, akin to human society, has been a long-standing endeavor for ...
A Survey on Self-Evolution of Large Language ModelsO网页链接本文是一篇关于大型语言模型自进化的调查报告。大型语言模型(LLM)在多个领域和智能代理应用中取得了显著的进步。然而,目前通过人类或外部模型监督学习的LLM成本高昂,并且随着任务复杂性和多样性的增加,可能会遇到性能瓶颈。为了解决这个问题,使LLM能够自主地...
A Survey on Model Compression for Large Language Models O网页链接ChatPaper综述:大语言模型(LLMs)的庞大规模和计算需求给实际部署带来的挑战,尤其是在资源有限的环境中。鉴于这些挑战变得越来越重要,模型压缩领域已经成为缓解这些限制的重要研究领域。本文提供了一份全面的调查报告,重点介绍了专门为LLMs定制的模型...
背景:OpenAI最近放出了Devday的闭门会视频,其中"A Survey of Techniques for Maximizing LLM Performance"(精进大型语言模型性能的各种技巧)是非常有价值的,本文对这次分享做摘要。 视频:https://www.youtube.com/watch?v=ahnGLM-RC1Y&ab_channel=OpenAI ...
A Survey on LLM-generated Text Detection: Necessity, Methods, and Future Directions, arXiv 2023.10 [Paper] [GitHub] Detecting ChatGPT: A Survey of the State of Detecting ChatGPT-Generated Text, arXiv 2023.09 [Paper] The Science of Detecting LLM-Generated Texts, arXiv 2023.02 [Paper] ...