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Mitigating Cross-Modal Hallucinations by Correcting Modality Misrouting in Omnimodal LLMs
Omnimodal large language models (OLLMs) are susceptible to cross-modal hallucinations under audio-visual interference. We find that, for a substantial fraction of incorrect joint predictions, the question-relevant unimodal branch can still recover the correct answer, suggesting that task-relevant ev
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