FastOCR: Dynamic Visual Fixation via KV Cache Pruning for Efficient Document Parsing

In three linesFastOCR introduces a training-free framework to accelerate OCR on Vision-Language Models by exploiting dynamic visual fixation. Through KV cache pruning, the model reduces visual tokens processed to 5% per decoding step while retaining 98% accuracy on Qwen2.5-VL, achieving 3.0× attention latency reduction.

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