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Research questionHow can document parsing remain accurate on difficult pages while running efficiently on limited GPUs?Document parsing must recover text, formulas, tables, and structure from varied pages, but complex layouts can increase errors and decoding cost. These costs make accurate OCR harder to deploy on modest hardware.
AI
Computer Vision
Evaluation & Benchmarks
Inference Optimization
Machine Learning
Multimodal Models
Research Paper
Small / On-device Models
Technology
Latest papersRecent research connected to this question, newest first.Jina-OCR-v1: Efficient Document Parsing with Speculative Decoding and Dense Verifiable RewardsThe source describes an end-to-end document parsing model using a compressed-vision encoder, a 3B mixture-of-experts decoder, speculative decoding with greedy verification, and post-training on difficult documents with dense structural rewards. It reports results on OmniDocBench v1.6 and olmOCR-Bench, including throughput comparisons and measurements on an NVIDIA L4; these results do not establish performance beyond the reported benchmarks and hardware settings.research paper · Sep 2, 2026
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