搜索结果：生成式引擎优化

ContextMax is a browser-based tool that enables developers to create precise context sets for LLMs by specifying relevant files, functions, and workflows, ensuring privacy and efficiency without uploa

Open Deep Research is an open-source implementation of OpenAI's Deep Research experiment that uses Firecrawl for web search/extraction with reasoning models for structured data analysis. 原文翻译： Open Deep Research 是 OpenAI Deep Research 实验的开源实现，使用 Firecrawl 进行网络搜索/提取，并结合推理模型进行结构化数据分析。

GPT-3 demonstrates that scaling language models to 175 billion parameters enables few-shot learning across diverse NLP tasks without task-specific fine-tuning, achieving competitive performance through text-only interaction. 原文翻译： GPT-3通过将语言模型扩展到1750亿参数，实现了跨多种NLP任务的少样本学习，无需任务特定微调，仅通过文本交互即可达到竞争性性能。

This article explores an alternative approach to the Model Context Protocol (MCP) for integrating tools with Large Language Models (LLMs) by leveraging existing OpenAPI servers. It proposes a simpler, more intuitive method that uses structured HTTP API definitions as tool inputs, requiring only minimal authentication flow additions. The implementation is demonstrated through a concise Scala script, focusing on core tool integration while omitting MCP's broader features like prompts and resources. 原文翻译： 本文探讨了一种替代模型上下文协议（MCP）的方法，通过利用现有的OpenAPI服务器为大型语言模型（LLM）集成工具。它提出了一种更简单、更直观的方法，使用结构化的HTTP API定义作为工具输入，仅需添加最小的身份验证流程。通过一个简洁的Scala脚本演示了实现，专注于核心工具集成，同时省略了MCP更广泛的功能，如提示和资源。

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。

This comprehensive 2026 ranking analyzes major LLMs across reasoning, coding, math, agentic, software engineering, and chat benchmarks, providing detailed performance scores and pricing comparisons for technical professionals. 原文翻译： 这份全面的2026年排名分析了主要大语言模型在推理、编码、数学、代理、软件工程和聊天基准测试中的表现，为技术专业人士提供详细的性能得分和定价对比。

The Boswell Test is an automated framework for comparative analysis of Large Language Models (LLMs) through peer-review evaluation, where models grade each other's essays across multiple domains to calculate a comprehensive Boswell Quotient score. 原文翻译： Boswell测试是一个自动化框架，通过同行评审评估对大语言模型进行对比分析，模型在多个领域相互评分论文，以计算全面的Boswell商数得分。

Beyin is a local-first engine for building reusable knowledge packs from various sources like videos, articles, and local files. It integrates with MCP-compatible AI agents (e.g., Claude Code, Codex) and supports fully offline workflows with Ollama, keeping your data private and reusable across tools. 原文翻译： Beyin 是一个本地优先的引擎，用于从视频、文章和本地文件等多种来源构建可重复使用的知识包。它与 MCP 兼容的 AI 代理（如 Claude Code、Codex）集成，并支持通过 Ollama 实现完全离线工作流，确保您的数据在跨工具使用时保持私密和可重用。

xmllm is a JavaScript utility that extracts structured data from LLMs using a flexible XML-based approach, offering resilience to errors and provider-agnostic compatibility. 原文翻译： xmllm 是一个 JavaScript 工具，通过灵活的基于 XML 的方法从大型语言模型中提取结构化数据，具有容错性和提供商无关的兼容性。