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CoSD: Collaborative Stance Detection with Contrastive Heterogeneous Topic Graph Learning
To address these challenges, we present a novel collaborative stance detection framework called (CoSD) which leverages contrastive heterogeneous topic graph learning to learn topic-aware semantics and collaborative signals among texts, topics, and stance labels for enhancing stance detection.
Graph Neural Networks: Taxonomy, Advances and Trends
Graph neural networks provide a powerful toolkit for embedding real-world graphs into low-dimensional spaces according to specific tasks.
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