Baidu Open-Sources Unlimited OCR 2 Document Parsing Model
Baidu has open-sourced Unlimited OCR 2, which uses a new SR-SWA mechanism to compress the attention interaction between text and vision into a fixed-size working reference, thereby parsing documents of almost any length within a limited context window. Baidu says that as documents grow longer, per-step decoding latency and memory usage remain nearly constant, and that the model achieves SOTA performance on MPDocBench and MarathonDocBench, which cover documents ranging from dozens to hundreds of pages.
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SelectedAI score 62
The official release presents the SR-SWA mechanism and results on two long-document benchmarks, offering insight into the context and latency trade-offs of long-document OCR.
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Unlimited OCR 2 is here, and it's open source. 📖 ✨
Longer documents can mean a lot more attention computation. Our new SR-SWA mechanism keeps that in check by condensing text-visual attention interactions into a fixed-size set of working references.
Here's what it delivers: - Document parsing at virtually any length, within a finite context window - Nearly constant per-step decoding latency and memory footprint as documents grow longer - State-of-the-art performance on MPDocBench and MarathonDocBench, covering documents from dozens to hundreds of pages
Check out the model here ↓