Papers by Gos Micklem

1 papers
HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs (2024.findings-emnlp)

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Challenge: Existing methods to learn informative data representations on text-attributed hypergraphs struggle to capture full extent of hypergraph structural information and rich linguistic attributes inherent in the nodes attributes.
Approach: They propose to augment a pre-trained BERT model with specialized hypergraph-aware layers for the task of node classification.
Outcome: The proposed model outperforms existing methods on five challenging text-attributed hypergraph node classification benchmarks.

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