English(EN) A 1.3B OCR model just hit 93.68 on real-world document parsing and there's now an AI judge for OCR errors

OpenBMB发布新的OCR模型及准确性裁判

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 16:21

OpenBMB发布了两个专注于改进光学字符识别（OCR）的开源模型。MiniCPM-OCR 1.0是一个拥有13亿参数的模型，在Real5-OmniDocBench真实世界文档解析基准上达到了93.68%的准确率，并通过DSpark解码加速得到增强。与之配套的是MiniCPM-OCR Jev，一个拥有20亿参数的模型，可作为OCR质量裁判，能够评估OCR输出在公式和表格等复杂元素上的准确性，并达到了0.936的AUROC。 AI

影响这些模型有望提高各种应用中文档处理的准确性和可靠性。

排序理由发布了具有基准性能的新开源模型。[lever_c_demoted from research: ic=1 ai=1.0]

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 1 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 发布了具有基准性能的新开源模型。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: model release, product; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Same-day; Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

r/LocalLLaMA TIER_1 English(EN) · /u/Equivalent-Grass-527 · 2026-10-27 16:21

一个13亿参数的OCR模型在真实世界文档解析中达到93.68%，现在有了用于OCR错误的AI法官

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1xgx26j/a_13b_ocr_model_just_hit_9368_on_realworld/"> <img alt="A 1.3B OCR model just hit 93.68 on real-world document parsing and there's now an AI judge for OCR errors" src="https://external-preview.redd.it/…

本文如何被排名

报道来源 [1]

一个13亿参数的OCR模型在真实世界文档解析中达到93.68%，现在有了用于OCR错误的AI法官

相关实体

相关话题