Papers by Md. Mahmudul Hasan

1 papers
GraDeT-HTR: A Resource-Efficient Bengali Handwritten Text Recognition System utilizing Grapheme-based Tokenizer and Decoder-only Transformer (2025.emnlp-demos)

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Challenge: Bengali is the sixth most spoken language in the world, but handwritten text recognition systems for the language are underdeveloped.
Approach: They propose a Bengali handwritten text recognition system that uses a decoder-only transformer to address the unique challenges of Bengali script.
Outcome: The proposed system significantly improves on existing tokenizers on Bengali script.

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