Following this, the introduction of large language models (LLMs) such as GPT-4 and BERT has lifted the standard for this task, promoting them to new heights of performance and capacity. Our survey provides a detailed review of the evolutionary phases of Text-to-SQL parsing. Initially, we ...
尽管检索增强模型已经出现,并且有很大的潜力,但它们也因为不能成为一个通用解决方案而受到批评 [70, 103],因为不加选择地将与LLMs无关的段落与LLMs相结合可能会覆盖LLMs已经具备的潜在正确知识,并导致错误的回复 [93]。Thakur等人 [139]提供了一个人工标注的数据集,以帮助评估LLMs对外部检索知识错误的鲁棒性,并...
Add a new survey about LLM&Text2SQL (2024-arXiv) A Survey on Employing Large Language Models for Text-to-SQL Tasks Link: https://arxiv.org/pdf/2407.15186 add a new survey about LLM&Text2SQL 60fa62e junewgl approved these changes Aug 19, 2024 View reviewed changes Collaborator junew...
: A Survey 文章链接:arxiv.org/pdf/2311.0791 问题:这篇文章提出了当前大型语言模型(LLMs)所面临的问题:它们存在幻觉现象,即在生成文本时会产生与事实不符或虚构的内容。LLMs在模型训练过程中通过大量数据学习语言模式和关联,但由于其中可能存在的知识缺失、误导信息、偏见以及上下文依赖性,导致模型产生不准确但看似...
A Survey of LLM Surveys Large language models (LLMs) are making sweeping advances across many fields of artificial intelligence. As a result, research interest and progress in LLMs have exploded. There are now hundreds of research papers on LLMs published in various conferences or posted to ope...
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 ...
LLMs之Prompt:《The Prompt Report: A Systematic Survey of Prompting Techniques》翻译与解读 导读:这篇论文主要描述了目前常用的自然语言输入技术—"提示"(prompting)。论文还收集了近1.6万篇与提示技术相关的文献,并使用机器学习算法分析这些文献,提取出58种文本提示技术和40多种多媒体提示技术。论文重点介绍了上下文...
LLM之RAG:《Retrieval-Augmented Generation for Large Language Models: A Survey大型语言模型的检索增强生成研究综述》翻译与解读 导读:这篇论文主要围绕信息检索增强生成(Retrieval Augmented Generation,简称RAG)技术进行概述和分析。 背景痛点: >> 大语言模型(LLM)在处理知识密集型任务和回答离线知识更丰富的问题时面临...
LLM4Drive: A Survey of Large Language Models for Autonomous Driving 摘要 1.介绍 2.Motivation of LLM4AD 3.Application of LLM4AD 3.1Planning & Control 3.2 Perception 3.3 Question Answering 3.4 Generation 3.5 Evaluation & Benchmark 4.Datasets in LLM4AD ...
{ "documents": [ { "language": "string", "id": "string", "text": "string" } ] } The Response area displays information based on the HTTP response for the action. Select Add default response. Specify the response body, and then select Import. As we did for the request body, we...