A 2B-parameter model trained with RL on verifiable LaTeX unit tests produces more compilable page-to-LaTeX reconstructions than prior OCR systems across structural and compilation metrics.
Lightonocr: A 1b end-to-end multilingual vision-language model for state-of-the-art ocr.arXiv preprint arXiv:2601.14251
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GlotOCR Bench shows that OCR models perform well on fewer than 10 scripts and fail to generalize beyond about 30, with results tracking pretraining coverage and models hallucinating from known scripts on unfamiliar ones.
RTPrune introduces a reading-twice inspired two-stage pruning technique for DeepSeek-OCR that retains 84.25% tokens while delivering 99.47% accuracy and 1.23x faster prefill on OmniDocBench.
citing papers explorer
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TexOCR: Advancing Document OCR Models for Compilable Page-to-LaTeX Reconstruction
A 2B-parameter model trained with RL on verifiable LaTeX unit tests produces more compilable page-to-LaTeX reconstructions than prior OCR systems across structural and compilation metrics.
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GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts
GlotOCR Bench shows that OCR models perform well on fewer than 10 scripts and fail to generalize beyond about 30, with results tracking pretraining coverage and models hallucinating from known scripts on unfamiliar ones.
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RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference
RTPrune introduces a reading-twice inspired two-stage pruning technique for DeepSeek-OCR that retains 84.25% tokens while delivering 99.47% accuracy and 1.23x faster prefill on OmniDocBench.