Papers with graph neural network layers

1 papers
Towards Few-shot Entity Recognition in Document Images: A Graph Neural Network Approach Robust to Image Manipulation (2024.lrec-main)

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Challenge: Existing methods for named entity recognition from document images are limited in few-shot settings.
Approach: They propose a framework which leverages the topological adjacency relationship among tokens by learning layout information with graph neural networks.
Outcome: The proposed framework outperforms baselines under different few-shot settings and shows better performance to image manipulations.

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