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附录B 参考资料与延伸阅读

本附录整理了书中引用的论文、文章、文档和其他学习资源，按主题分类。

📚 核心论文

Transformer & Attention

Attention is All You Need (2017)
Vaswani et al.
https://arxiv.org/abs/1706.03762
Transformer架构的开创性论文

BERT: Pre-training of Deep Bidirectional Transformers (2018)
Devlin et al.
https://arxiv.org/abs/1810.04805
双向预训练语言模型

Language Models are Few-Shot Learners (2020)
Brown et al. (GPT-3)
https://arxiv.org/abs/2005.14165
Few-Shot Learning的里程碑

Prompt Engineering

Chain-of-Thought Prompting (2022)
Wei et al.
https://arxiv.org/abs/2201.11903
思维链提示技术

ReACT: Synergizing Reasoning and Acting (2023)
Yao et al.
https://arxiv.org/abs/2210.03629
ReACT Agent架构

RAG & Retrieval

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (2020)
Lewis et al.
https://arxiv.org/abs/2005.11401
RAG的原始论文

Dense Passage Retrieval for Open-Domain QA (2020)
Karpukhin et al.
https://arxiv.org/abs/2004.04906
密集向量检索

📖 推荐书籍

《Designing Data-Intensive Applications》
Martin Kleppmann
https://dataintensive.net/
构建可扩展系统的必读书籍

《Building a Second Brain》
Tiago Forte
https://www.buildingasecondbrain.com/
个人知识管理方法论

《The Pragmatic Programmer》
David Thomas & Andrew Hunt
软件工程实践指南

《How to Take Smart Notes》
Sönke Ahrens
卡片笔记法，知识管理的经典

🌐 官方文档

LLM Providers

OpenAI API Documentation
https://platform.openai.com/docs
GPT-4、Embedding等API文档

Anthropic Claude Documentation
https://docs.anthropic.com/
Claude API和Prompt Engineering指南

Google Gemini API
https://ai.google.dev/docs
Gemini模型文档

Tools & Frameworks

LangChain Documentation
https://python.langchain.com/
LLM应用开发框架

LlamaIndex Documentation
https://docs.llamaindex.ai/
RAG和数据索引框架

Cursor Documentation
https://docs.cursor.com/
Cursor IDE官方文档

OpenAI Agents SDK
https://openai.github.io/openai-agents-python/
Agent tracing、guardrails、handoff 和工具调用参考

OpenAI Agent Evals
https://platform.openai.com/docs/guides/agent-evals
Agent 质量评估与 trace grading

Model Context Protocol Documentation
https://modelcontextprotocol.io/
MCP 协议、Server 和 Client 文档

Anthropic MCP Documentation
https://docs.anthropic.com/en/docs/mcp
Claude 与 MCP 集成说明

LangSmith Documentation
https://docs.langchain.com/langsmith/
Agent observability、tracing 和 evaluation

🎓 在线课程

DeepLearning.AI - ChatGPT Prompt Engineering
https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/
Andrew Ng的Prompt Engineering课程

LangChain for LLM Application Development
https://www.deeplearning.ai/short-courses/langchain-for-llm-application-development/
LangChain实战课程

Building Systems with the ChatGPT API
https://www.deeplearning.ai/short-courses/building-systems-with-chatgpt/
构建ChatGPT系统

📝 技术博客

个人博客

Lil’Log (Lilian Weng - OpenAI)
https://lilianweng.github.io/
高质量的AI技术博客

Jay Alammar’s Blog
https://jalammar.github.io/
可视化解释深度学习

Andrej Karpathy’s Blog
https://karpathy.github.io/
AI领域领军人物的博客

公司博客

OpenAI Blog
https://openai.com/blog
GPT、ChatGPT等产品发布

Anthropic Research
https://www.anthropic.com/research
Claude和Constitutional AI

DeepMind Blog
https://deepmind.google/discover/blog/
AlphaGo、Gemini等研究

🛠️ 工具资源

Vector Databases

Chroma
https://www.trychroma.com/
轻量级向量数据库

Pinecone
https://www.pinecone.io/
托管向量数据库服务

Weaviate
https://weaviate.io/
开源向量搜索引擎

Milvus
https://milvus.io/
高性能向量数据库

Embedding Models

Sentence Transformers
https://www.sbert.net/
开源Embedding模型库

Voyage AI
https://www.voyageai.com/
专业Embedding服务

Cohere Embed
https://cohere.com/embed
多语言Embedding API

Knowledge Management

Obsidian
https://obsidian.md/
本地优先的知识管理工具

Notion
https://www.notion.so/
在线协作知识库

Roam Research
https://roamresearch.com/
双向链接笔记

🎯 实战项目

Open Source Projects

AutoGPT
https://github.com/Significant-Gravitas/AutoGPT
自主Agent实现

LangChain Templates
https://github.com/langchain-ai/langchain/tree/master/templates
LangChain应用模板

PrivateGPT
https://github.com/imartinez/privateGPT
私有RAG系统

Quivr
https://github.com/StanGirard/quivr
个人知识管理Agent

📊 研究资源

Papers with Code

Papers with Code - NLP
https://paperswithcode.com/area/natural-language-processing
NLP论文和代码

Hugging Face Papers
https://huggingface.co/papers
每日AI论文推荐

Benchmarks

MMLU (Massive Multitask Language Understanding)
https://github.com/hendrycks/test
LLM综合能力评测

HumanEval
https://github.com/openai/human-eval
代码生成能力评测

MTEB (Massive Text Embedding Benchmark)
https://github.com/embeddings-benchmark/mteb
Embedding模型评测

🎤 视频资源

YouTube Channels

Andrej Karpathy
https://www.youtube.com/@AndrejKarpathy
从零构建GPT等教学视频

3Blue1Brown
https://www.youtube.com/@3blue1brown
神经网络可视化讲解

Two Minute Papers
https://www.youtube.com/@TwoMinutePapers
AI论文快速解读

📰 资讯订阅

Newsletters

The Batch (DeepLearning.AI)
https://www.deeplearning.ai/the-batch/
每周AI新闻

Import AI (Jack Clark)
https://importai.substack.com/
AI研究进展

The Gradient
https://thegradient.pub/
深度AI评论

Podcasts

Lex Fridman Podcast
https://lexfridman.com/podcast/
AI领域深度访谈

The TWIML AI Podcast
https://twimlai.com/
机器学习技术讨论

🔍 搜索引擎

Perplexity AI
https://www.perplexity.ai/
AI驱动的搜索引擎

Phind
https://www.phind.com/
面向开发者的AI搜索

📚 延伸阅读建议

初学者路径

  1. 先读 OpenAI 和 Anthropic 的 Prompt Engineering 指南
  2. 学习 LangChain 或 LlamaIndex 框架
  3. 实践小型 RAG 项目
  4. 阅读经典论文（Transformer、BERT、GPT-3）

进阶路径

  1. 深入学习 ReACT、Chain-of-Thought 等论文
  2. 研究生产级 Agent 系统设计
  3. 优化 RAG 系统性能
  4. 贡献开源项目

专家路径

  1. 阅读最新研究论文
  2. 实验新模型和技术
  3. 构建领域特定 Agent 系统
  4. 分享经验和最佳实践

本参考资料持续更新，欢迎补充