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Rohan Paul@rohanpaul_ai
OXR makes parsing failures part of the training process.
During post-training (OXR is the first document parser to use RSI here), a VLM evaluates its outputs, rollout disagreements flag uncertainty, and a separate clustering model groups the causes;
those findings then guide targeted data generation for the next round, and the 1.3B model that comes out of it sits first on olmOCR-Bench, OmniDocBench and DocParsingBench while running 3.05× GLM-OCR's throughput on a single RTX PRO 6000, the fastest open-source result in the speed comparison.
Worth studying (Github link in comment)
Beyond OCR. Meet OXR.
Only 1.3B. Open source.
#1 on olmOCR-Bench, OmniDocBench & DocParsingBench🏆
#1 in parsing speed among open-source models⚡
RSI-powered. A first in document parsing.
Turn documents into Agent-Friendly data.
If OXR helps, give us a star on GitHub! 🌟 https://t.co/kQlsq8oIdN
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