PDF is one of the hardest inputs for RAG: scans require OCR, tables get flattened, and multi-column layouts scramble reading order. This guide breaks the workflow into four stages—extract text, preserve structure, chunk and index, then answer questions—and explains the pitfalls and tool choices at each step.
上下文窗口从几千涨到百万 token，但「能装下」不等于「用得好」。本文讲清长上下文的三类真实失效模式——中间信息被忽略、干扰内容降低准确率、成本和延迟飙升，以及什么时候该用长上下文、什么时候该用 RAG。
召回负责「别漏」，重排负责「排对」。本文讲清 Cross-Encoder 重排和向量检索的本质区别、什么时候值得加 Rerank、模型怎么选，以及一份可直接套用的两阶段检索配置。
A comparison of Perplexity, ChatGPT Search, Gemini, and You.com across citation quality, freshness, understanding of complex questions, and the Chinese-language search experience.
Compare ElevenLabs, OpenAI TTS, Azure Speech, and Fish Audio on voice naturalness, cloning quality, latency, pricing, and API usability.
切分是 RAG 里最便宜也最容易被忽视的环节。本文对比固定长度、递归、结构化、语义切分四种策略和不同 Chunk Size 的实际表现，给出一套可以直接抄的默认配置和调优流程。
When RAG gives incorrect or off-target answers, the model usually is not the problem—the retrieval pipeline is. This guide identifies 10 common engineering causes across ingestion, retrieval, and generation, with practical fixes and ways to validate each one.
Vector search understands meaning but struggles with model numbers and identifiers. BM25 matches exact words but misses paraphrases. Hybrid search runs both and combines the results. This guide explains their tradeoffs, reciprocal rank fusion, and which approach fits each use case.
A hands-on comparison of Sora, Runway, Kling, Pika, and Hailuo across image quality, motion consistency, control, cost, and commercial workflows to help video creators choose the right tool.
Compare leading AI writing tools for brand copy, long-form content, team collaboration, Chinese writing, and content SEO to find the best fit for marketers, operators, and creators.
别只看排行榜——公开榜单和你的真实场景可能毫不相关。本文给出一套自己动手评测大模型的方法：怎么建评估集、定哪些评分维度、用 LLM 当裁判要注意什么，以及一份可直接套用的评分 Prompt 模板。
幻觉不是 bug，而是「预测下一个词」这套机制的必然副产品。本文从原理讲清模型为什么会一本正经地胡说，再落到检索、约束、校验、拒答四类工程手段，说明为什么幻觉无法根除、只能管控。
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