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ERASE: Eliminating Redundant Visual Tokens via Adaptive Two-Stage Token Pruning
Recent advances in Vision-Language Models (VLMs) enable large language models (LLMs) to process high-resolution images, significantly improving real-world multimodal understanding. However, this capability introduces a large number of vision tokens, incurring substantial computational overhead. To m
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