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  # LayoutLMv2
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  **Multimodal (text + layout/format + image) pre-training for document AI**
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- [Microsoft Document AI](https://www.microsoft.com/en-us/research/project/document-ai/) | [Github Repository](https://github.com/microsoft/unilm/tree/master/layoutlmv2)
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  ## Introduction
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  LayoutLMv2 is an improved version of LayoutLM with new pre-training tasks to model the interaction among text, layout, and image in a single multi-modal framework. It outperforms strong baselines and achieves new state-of-the-art results on a wide variety of downstream visually-rich document understanding tasks, including , including FUNSD (0.7895 β†’ 0.8420), CORD (0.9493 β†’ 0.9601), SROIE (0.9524 β†’ 0.9781), Kleister-NDA (0.834 β†’ 0.852), RVL-CDIP (0.9443 β†’ 0.9564), and DocVQA (0.7295 β†’ 0.8672).
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  # LayoutLMv2
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  **Multimodal (text + layout/format + image) pre-training for document AI**
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+ [Microsoft Document AI](https://www.microsoft.com/en-us/research/project/document-ai/) | [GitHub](https://github.com/microsoft/unilm/tree/master/layoutlmv2)
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  ## Introduction
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  LayoutLMv2 is an improved version of LayoutLM with new pre-training tasks to model the interaction among text, layout, and image in a single multi-modal framework. It outperforms strong baselines and achieves new state-of-the-art results on a wide variety of downstream visually-rich document understanding tasks, including , including FUNSD (0.7895 β†’ 0.8420), CORD (0.9493 β†’ 0.9601), SROIE (0.9524 β†’ 0.9781), Kleister-NDA (0.834 β†’ 0.852), RVL-CDIP (0.9443 β†’ 0.9564), and DocVQA (0.7295 β†’ 0.8672).
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