| Challenge: | olmOCR is a fully open OCR system developed through iterative public releases and community feedback. |
| Approach: | They propose an open OCR system that combines a 7B vision-language model trained in two stages: finetuning and reinforcement learning with visual unit tests. |
| Outcome: | The proposed system achieves state-of-the-art performance among open systems and proprietary APIs at a fraction of the cost. |
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Siming Huang, Tianhao Cheng, Jason Klein Liu, Weidi Xu, Jiaran Hao, Liuyihan Song, Yang Xu, Jian Yang, Jiaheng Liu, Chenchen Zhang, Linzheng Chai, Ruifeng Yuan, Xianzhen Luo, Qiufeng Wang, YuanTao Fan, Qingfu Zhu, Zhaoxiang Zhang, Yang Gao, Jie Fu, Qian Liu, Houyi Li, Ge Zhang, Yuan Qi, Xu Yinghui, Wei Chu, Zili Wang
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