Unverified50% confidenceFactExact time
There are three main technical approaches to injecting external knowledge into large language models: fine-tuning, retrieval-augmented generation (RAG), and structured semantic layer/ontology injection.
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10/5/2026
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UnverifiedLarge model application development can be divided into three progressive levels: prompt engineering, RAG retrieval-augmented generation, and model fine-tuning.77% similarUnverifiedThere are two technical approaches to vertical-domain knowledge injection: one is injecting domain knowledge at the foundation model level through fine-tuning, which requires large amounts of annotated data and offers low flexibility; the other is keeping the foundation model unchanged and dynamically injecting knowledge at inference time through tool calls, RAG, or structured prompts, which offers higher flexibility but places greater demands on prompt engineering.77% similarUnverifiedThe industry best practice is to combine fine-tuning with RAG—first fine-tuning to give the model domain understanding capability, then supplementing the latest dynamic knowledge through RAG.76% similarUnverified三种RAG路线并非互斥，实际工程中可采用混合架构：用向量检索做初步召回，用图谱结构做关系推理，用编译层做知识管理和溯源75% similarUnverifiedFine-tuning is suitable for teaching a model a specific output style or domain tone, while RAG achieves immediate-update-ready results through an external knowledge base, and the two are often used in combination in engineering.75% similar
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