Papers with multi-modal pre-training model

2 papers
TableVLM: Multi-modal Pre-training for Table Structure Recognition (2023.acl-long)

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Challenge: Tables are useful for displaying data in an organized manner, but they are difficult to extract from images because of their structure, notation, and representation.
Approach: They propose a multi-modal pre-training model for table structure recognition that captures table structure-related features by multiple unsupervised objectives inspired by masked visual-language modeling.
Outcome: The proposed model improves tree-editing-distance-score on ComplexTable by 1.97% .
LayoutMask: Enhance Text-Layout Interaction in Multi-modal Pre-training for Document Understanding (2023.acl-long)

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Challenge: Pre-trained models on document images with transformer-based backbones have led to significant performance gains in this field.
Approach: They propose a multi-modal pre-training model that combines text, layout and image . they propose to use local 1D position instead of global 1D positions as layout input .
Outcome: The proposed model can achieve state-of-the-art results on a wide variety of VrDU problems.

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