Unverified50% confidenceTradeoffExact time
Specialized models fine-tuned for specific domains or built on retrieval-augmented generation (RAG) can achieve equal or even superior results in specific workflows at a smaller parameter scale and lower inference cost.
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Long-term
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10/10/2026
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UnverifiedThe 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.80% 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.77% similarUnverifiedLarge model application development can be divided into three progressive levels: prompt engineering, RAG retrieval-augmented generation, and model fine-tuning.73% similarUnverified从历史工单自动提炼标准化流程的系统通常采用RAG（检索增强生成）架构，通过向量化和语义检索找到相关案例，再由LLM生成标准化流程以降低幻觉风险73% similarUnverified模板对齐能力在技术上依托RAG或Few-shot Learning机制实现，将企业模板作为上下文示例注入模型推理过程72% similar
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