AI RESEARCH
Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models
arXiv CS.AI
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ArXi:2605.28828v1 Announce Type: cross Large Language Models (LLMs) achieve impressive performance across many tasks but remain prone to hallucination, especially in long-form generation where redundant retrieved contexts and lengthy reasoning chains amplify factual errors. Recent studies highlight a critical phenomenon: the closer key information appears to the model outputs, the higher the factual accuracy.