AINeutralarXiv – CS AI · 10h ago6/10
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Noise-Aware In-Context Learning for Hallucination Mitigation in ALLMs
Researchers propose Noise-Aware In-Context Learning (NAICL), a plug-and-play method to reduce hallucinations in auditory large language models without expensive fine-tuning. The approach uses a noise prior library to guide models toward more conservative outputs, achieving a 37% reduction in hallucination rates while establishing a new benchmark for evaluating audio understanding systems.