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#text-attributed-graphs News & Analysis

2 articles tagged with #text-attributed-graphs. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles
AINeutralarXiv – CS AI · 3d ago6/10
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GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback

Researchers propose GNN-as-Judge, a framework combining Large Language Models with Graph Neural Networks to improve learning on text-attributed graphs in low-resource settings. The approach uses collaborative pseudo-labeling and weakly-supervised fine-tuning to generate reliable labels while reducing noise, demonstrating significant performance gains when labeled data is scarce.

AINeutralarXiv – CS AI · Mar 24/107
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Language Models as Messengers: Enhancing Message Passing in Heterophilic Graph Learning

Researchers propose LEMP4HG, a new language model-enhanced approach for improving graph neural networks on heterophilic graphs where connected nodes have different characteristics. The method leverages language models to better understand semantic relationships between text-attributed nodes, outperforming existing methods while maintaining efficiency through selective message enhancement.