← Back to news
ai

RAG precision tuning can quietly cut retrieval accuracy by 40%, putting agentic pipelines at risk

Enterprise teams that fine-tune their RAG embedding models for better precision may be unintentionally degrading the retrieval quality those pipelines depend on, according to new research from Redis.The paper, "Training for Compositional Sensitivity Reduces Dense Retrieval Generalization,"