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Existing explainability methods misrepresent multimodal decision-making, often conflating genuine reasoning with shallow shortcuts.
Even the best MLLMs still fall far short of human performance in collaborative spatial reasoning, revealing a critical gap in their ability to build and maintain shared mental models through dialogue.
