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SLICEChat: Progressive In-Encoder Token Pruning for Whole-Slide Pathology Language Models
Whole-slide pathology images (WSIs) contain gigapixel-scale visual content, creating a major scalability challenge for slide-level multimodal large language models (MLLMs). Existing approaches process thousands of patch tokens and typically apply compression only after slide encoding, leaving multim
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