Prior work has leveraged two approaches to mitigate these problems: tool-use and Retrieval Augmented Generation (RAG). In tool-use, the LLM is ��ne-tuned to produce a markup language which intersperses natural text with function calls to external tools.4 To address hallucinations, tools mi...
最后,该论文讲了一些研究前景,包括未来挑战、多模态的扩展以及RAG基础设施及其生态系统的进展[^1]。 论文地址: Retrieval-Augmented Generation for Large Language Models: A Survey | PPT 注: 主要是了解RAG的发展过程(召回率),以及对相关子模块领域的现阶段了解,如果感兴趣,通过索引到论文引用处进一步了解。(...
模块化RAG是对传统RAG框架的一种扩展和改进,它提供了更大的多样性和灵活性。模块化RAG不再局限于简单的索引、检索和生成过程,而是通过引入新的模块和方法,使得整个RAG流程可以更加灵活地适应不同的应用场景和需求: 2.3.1. 新模块 (New Modules) 搜索模块 (Search Module): 与传统RAG中的相似性检索不同,搜索模块...
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection. [2023.10.17] [Arxiv] Towards reducing hallucination in extracting information from financial reports using Large Language Models. [2023.10.16] [Arxiv] In-Context Pretraining: Language Modeling Beyond Document Boundaries. ...
prompttransformersdatasettransformerdatasetsdataset-generationlanguage-modelragllmprompt-engineeringlargelanguagemodelretrieval-augmented-generation UpdatedMar 15, 2025 Jupyter Notebook This repo contains the resources, projects and documentation of mine while learning Large Language Model ...
“What is PRO?” response with RAG Ubuntu Pro is an additional stream of security updates and packages that meet compliance requirements, such as FIPS or HIPAA, on top of an Ubuntu LTS. It provides an SLA for security fixes for the entire distribution (‘main and universe’ packages) for ...
CRUD-RAG: a comprehensive Chinese benchmark for retrieval-augmented generation of large language models. 2024, arXiv preprint arXiv: 2401.17043 Lyu Y, Niu Z, Xie Z, Zhang C, Xu T, Wang Y, Chen E. Retrieve-plan-generation: an iterative planning and answering framework for knowledge-intensive...
Simplest LLM agents can function withoutMemory, but nearly every practical implementation will require some degree of memory. Used in the context of agents, memory means much more than Retrieval Augmented Generation (RAG), which is a favored technique ofaugmenting LLMs with enterprise knowledge. Memo...
本文对清华大学李国良教授团队论文《DB-GPT:Large Language Model Meets Database》进行解读,全文共6312字,预计阅读需要20至30分钟。 数字化时代背景下,数据已成为企业和社会发展的核心,数据库系统的性能与效率直接影响应用品质及响应速度。随着技术的持续演进,大型语言模型(LLMs)在自然语言处理领域取得了显著成就,其在...
在接收到这些输入后,LLMs进行推理并产生输出,包括生成的语言模型程序(Language Model Programs, LMPs)P和推理思想R。生成的LMP被发送到执行器在环境中执行,而推理思想帮助LLMs生成更合理的驾驶策略。不过要注意的是,这是一个通用概念,具体实现可能因不同应用而异。 人类指令和评估 人类的指令I和评估F直接以自然...