8 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.LG2025★ 8 cited
PyG 2.0: Scalable Learning on Real World Graphs
Matthias Fey, Jinu Sunil, Akihiro Nitta +10
PyG (PyTorch Geometric) has evolved significantly since its initial release, establishing itself as a leading framework for Graph Neural Networks. In this paper, we present Pyg 2.0…
cs.IR2025
Query-Aware Graph Neural Networks for Enhanced Retrieval-Augmented Generation
Vibhor Agrawal, Fay Wang, Rishi Puri
We present a novel graph neural network (GNN) architecture for retrieval-augmented generation (RAG) that leverages query-aware attention mechanisms and learned scoring heads to imp…
cs.LG2025
Relational Graph Transformer
Vijay Prakash Dwivedi, Sri Jaladi, Yangyi Shen +5
Relational Deep Learning (RDL) is a promising approach for building state-of-the-art predictive models on multi-table relational data by representing it as a heterogeneous temporal…