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Enhancing OCR Performance through Post-OCR Models: Adopting Glyph Embedding for Improved Correction
The study investigates the potential of post-OCR models to overcome limitations in OCR models and explores the impact of incorporating glyph embedding on post-OCR correction performance.
Evaluating the Robustness to Instructions of Large Language Models
The focus is on the robustness of instruction-tuned LLMs to seen and unseen tasks.
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