Papers by Ningbo Huang

1 papers
Pre-trained Semantic Interaction based Inductive Graph Neural Networks for Text Classification (2025.coling-main)

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Challenge: Existing methods for text classification have vanishing or exploding gradients when dealing with long sequences, making it difficult to handle long-distance dependencies.
Approach: They propose a graph neural network based on pre-trained semantic interaction called PaSIG . they construct a text-word heterogeneity graph and use context representation capability .
Outcome: The proposed model outperforms existing methods on five datasets and achieves state-of-the-art performance.

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