搜索结果：结构化数据

GraphRAG (Graphs + Retrieval Augmented Generation) is a technique for richly understanding text datasets by combining text extraction, network analysis, and LLM prompting and summarization into a single end-to-end system. 原文翻译： GraphRAG（图+检索增强生成）是一种通过将文本提取、网络分析、LLM提示和摘要整合到单一端到端系统中，来深入理解文本数据集的技术。

This survey provides a comprehensive overview of recent progress in LLM-empowered knowledge graph construction, systematically analyzing how LLMs reshape the classical three-layered pipeline of ontology engineering, knowledge extraction, and knowledge fusion. 原文翻译： 本综述全面概述了LLM赋能知识图谱构建的最新进展，系统分析了LLM如何重塑本体工程、知识抽取和知识融合的经典三层流程。

This research paper reveals new indirect prompt injection attack vectors that enable adversaries to remotely exploit LLM-integrated applications by injecting malicious prompts into retrieved data, demonstrating practical attacks against systems like Bing Chat and highlighting significant security vulnerabilities in current LLM deployments. 原文翻译： 本研究论文揭示了新的间接提示注入攻击向量，攻击者可通过在检索数据中注入恶意提示来远程利用LLM集成应用，展示了针对Bing Chat等系统的实际攻击，并突显了当前LLM部署中的重大安全漏洞。

RAGstack is an open-source solution for deploying private ChatGPT alternatives within your VPC, connecting to organizational knowledge bases, and supporting models like Llama 2, Falcon, and GPT4All with vector database integration. 原文翻译： RAGstack是一个开源解决方案，用于在您的VPC内部署私有ChatGPT替代方案，连接组织知识库，并支持Llama 2、Falcon和GPT4All等模型，集成了向量数据库。

Cognee is an AI-powered knowledge engine that transforms data into living knowledge graphs, enabling adaptive AI agents that learn from feedback and improve over time. It replaces custom knowledge graphs and vector stores with a unified platform for retrieval and reasoning. 原文翻译： Cognee是一个AI驱动的知识引擎，可将数据转化为动态知识图谱，支持从反馈中学习并随时间改进的自适应AI代理。它用一个统一平台替代了自定义知识图谱和向量存储，用于检索和推理。

RAG (Retrieval-Augmented Generation) is a mainstream LLM application architecture that enhances answer accuracy by retrieving relevant information from external knowledge bases before generation, addressing issues like knowledge cutoff and hallucinations. 原文翻译： RAG（检索增强生成）是目前主流的LLM落地架构，通过在生成答案前从外部知识库检索相关信息，显著提升回答准确性，有效解决知识截止日期和幻觉问题。

This repository provides a comprehensive collection of tutorials and implementations for Generative AI agents, ranging from beginner conversational bots to advanced multi-agent systems, with 52+ practical examples and community-driven resources. 原文翻译： 本资源库提供了生成式AI智能体的全面教程和实现，涵盖从初学者对话机器人到高级多智能体系统，包含52+个实用示例和社区驱动的资源。

This paper comprehensively formalizes the problem of secret collusion in systems of generative AI agents, studying steganographic techniques that could enable unauthorized information sharing and proposing mitigation measures with an evaluation framework. 原文翻译：本文全面形式化了生成式AI代理系统中的秘密合谋问题，研究了可能促成未经授权信息共享的隐写技术，并提出了缓解措施和评估框架。

Google is integrating generative AI into Google Maps to provide conversational, personalized recommendations for places like restaurants and shops, initially available to Local Guides in the US. 原文翻译： 谷歌正在将生成式AI整合到谷歌地图中，为餐厅和商店等地点提供对话式、个性化的推荐，该功能最初在美国向本地向导开放。

This article provides a practical guide for software engineers transitioning into AI R&D roles, focusing on aligning generative AI prototypes with business value, educating stakeholders, and navigating organizational processes to successfully integrate research into product roadmaps. 原文翻译： 本文为软件工程师转型AI研发角色提供实用指南，重点介绍如何将生成式AI原型与商业价值对齐、教育利益相关者，以及通过组织流程成功将研究成果整合到产品路线图中。