Task-related visual token compression is feasible at the input stage of MLLMs by learning a lightweight CNN mapping from first-layer attention maps to explainability-derived token importance scores.
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Task-Related Token Compression in Multimodal Large Language Models from an Explainability Perspective
Task-related visual token compression is feasible at the input stage of MLLMs by learning a lightweight CNN mapping from first-layer attention maps to explainability-derived token importance scores.