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Tiramisu's tiered transformer architecture revolutionizes newspaper image understanding by explicitly modeling document hierarchy, outperforming traditional methods in reconstructing complex layouts.
Mamba-based OCR can process long paragraphs 1.4 to 4.5 times faster than Transformers, but struggles with handwriting due to data limitations.
Forget quadratic complexity: Mamba-based OCR rivals Transformer accuracy while halving inference time and scaling memory more efficiently, finally making paragraph-level historical text transcription practical.
Forget fine-tuning: this HTR model adapts to new handwriting styles in just a few shots, *without* any parameter updates.
