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Achieve robust multimodal fusion even with missing modalities by ensuring the fusion head always receives a complete, fixed-size input via learned proxy tokens.
D-LLM hallucinations aren't uniformly distributed across tokens or denoising steps; DynHD exploits this to boost detection accuracy and efficiency.
