Tag: retrieval-augmented generation

Document Re-Ranking to Improve RAG Relevance for Large Language Models

Document Re-Ranking to Improve RAG Relevance for Large Language Models

Document re-ranking improves RAG systems by filtering retrieved documents with deep semantic analysis, reducing hallucinations and boosting accuracy in large language model responses. It's essential for high-stakes applications like healthcare and legal AI.

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Search-Augmented Large Language Models: RAG Patterns That Improve Accuracy

Search-Augmented Large Language Models: RAG Patterns That Improve Accuracy

RAG patterns boost LLM accuracy by 35-60% by fetching real-time data before answering. Learn how hybrid search, query expansion, and recursive retrieval fix hallucinations and cut errors in enterprise AI.

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