一般来说，RAG 被公认是最有效的为 LLM 注入特定领域知识的方式。 然而，RAG 也有其不足之处。通常来说，在实际应用中，为确保能召回包含正确 ...

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本文中将重点介绍如何优化RAG系统，使其尽可能高效。我们从多个角度介绍RAG系统，深入了解其用途以及如何优化。 介绍 检索增强生成（RAG）模型通常被称为RAG系统，在AI行业得到极大的关注。这种模型背后的概念很简单：我们允许模型根据需要从单独的数据集 ...

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【新智元导读】RAG通过纳入外部文档可以辅助LLM进行更复杂的推理，降低问题求解所需的推理深度，但由于文档噪声的存在，其提升效果可能会受限。

Learn More Cohere has added multimodal embeddings to its search model, allowing users to deploy images to RAG-style enterprise search. Embed 3, which emerged last year, uses embedding models ...

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1. 为啥要提出VisRAG？ 检索增强生成（Retrieval-augmented generation, RAG） 已经成为解决LLM幻觉和知识更新的经典方案，典型的RAG流程是基于文本的（以下简称TextRAG），以分割后的文本作为检索单元。 但是在真实场景中，知识往往以多模态的形式出现，比如教科书 ...