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Concatenation MLLMs fuse vision late, while native architectures co-adapt modalities from the start, revealing fundamentally different cross-modal information flow.
Despite achieving 84.8% accuracy, multimodal models struggle with long-horizon reasoning in electrical circuits, revealing critical gaps in their understanding of physical conventions.
