olmOCR 2: Unit Test Rewards for Document OCR

Jake Poznanski, Luca Soldaini, Kyle Lo

olmOCR 2: Unit Test Rewards for Document OCR: 17 upvotes on Hugging Face Daily Papers, #13 of 37 papers on 2025-10-23. Day-by-day upvote history.

We present olmOCR 2, the latest in our family of powerful OCR systems for converting digitized print documents, like PDFs, into clean, naturally ordered plain text. olmOCR 2 is powered by olmOCR-2-7B-1025, a specialized, 7B vision language model (VLM) trained using reinforcement learning with verifiable rewards (RLVR), where our rewards are a diverse set of binary unit tests. To scale unit test creation, we develop a pipeline for generating synthetic documents with diverse and challenging layouts, known ground-truth HTML source code, and extracted test cases. We show that RL training on these test cases results in state-of-the-art performance on olmOCR-Bench, our English-language OCR benchmark, with the largest improvements in math formula conversion, table parsing, and multi-column layouts compared to previous versions. We release our model, data and code under permissive open licenses.

Paper page on Hugging Face · arXiv

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