Leveraging Discrete Semantic Prototypes for Representation Learning on Text-Attributed Graphs
Integrating Large Language Models (LLMs) with Graph Neural Networks (GNNs) has emerged as a dominant paradigm for representation learning on Text-Attributed Graphs (TAGs). Existing approaches face three primary challenges: the difficulty in distinguishing core semantic information from textual redun...
Kaydedildi:
| Asıl Yazarlar: | , , |
|---|---|
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
IEEE
2026-01-01
|
| Seri Bilgileri: | IEEE Access |
| Konular: | |
| Online Erişim: | https://ieeexplore.ieee.org/document/11373041/ |
| Etiketler: |
Etiket eklenmemiş, İlk siz ekleyin!
|