Omni-Modal LLMs Know More Than They Say

Omni-modal LLMs often perceive non-textual signals correctly but fail to express them in text outputs, a phenomenon termed knows-but-cannot-say. Token-level Modality Alignment (TMA) reveals that non-textual representations receive less attention and show lower alignment with response tokens than textual representations, causing uneven modality preferences.