Papers with vision transformer

2 papers
BornoDrishti: Leveraging Vision Encoders and Domain-Adaptive Learning for Bangla OCR on Diverse Documents (2026.eacl-industry)

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Challenge: Existing solutions for OCR for Bangla scripts are limited to single-domain processing.
Approach: They propose a unified OCR system that recognizes both printed and handwritten Bangla scripts within a single model.
Outcome: The proposed system achieves competitive accuracy across both domains and surpasses specialized uni-domain systems.
Pixology: Probing the Linguistic and Visual Capabilities of Pixel-based Language Models (2024.emnlp-main)

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Challenge: PIXEL is a vision transformer that has been pre-trained on rendered text . however, it is not able to outperform monolingual subwords like BERT .
Approach: They propose to use PIXEL as a vision transformer to train on rendered text to explore the gap between its visual and linguistic understanding.
Outcome: The proposed model outperforms monolingual subword models in most other contexts, but it lacks the linguistic knowledge to perform in language tasks.

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