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- W3197942012 abstract "Natural language processing for document scans and PDFs has the potential to enormously improve the efficiency of business processes. Layout-aware word embeddings such as LayoutLM have shown promise for classification of and information extraction from such documents. This paper proposes a new pre-training task called that can improve performance of layout-aware word embeddings that incorporate 2-D position embeddings. We compare models pre-trained with only language masking against models pre-trained with both language masking and position masking, and we find that position masking improves performance by over 5% on a form understanding task." @default.
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- W3197942012 date "2021-09-01" @default.
- W3197942012 modified "2023-09-27" @default.
- W3197942012 title "Position Masking for Improved Layout-Aware Document Understanding." @default.
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