activity
20242026
most citedPyG 2.0: Scalable Learning on Real World Graphs

8 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DB2026

SEAR: Schema-Based Evaluation and Routing for LLM Gateways

Zecheng Zhang, Han Zheng, Yue Xu

Evaluating production LLM responses and routing requests across providers in LLM gateways requires fine-grained quality signals and operationally grounded decisions. To address thi…

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.IR2024★ 1 cited

ContextGNN: Beyond Two-Tower Recommendation Systems

Yiwen Yuan, Zecheng Zhang, Xinwei He +10

Recommendation systems predominantly utilize two-tower architectures, which evaluate user-item rankings through the inner product of their respective embeddings. However, one key l…

cs.LG2024★ 3 cited

RelBench: A Benchmark for Deep Learning on Relational Databases

Joshua Robinson, Rishabh Ranjan, Weihua Hu +9

We present RelBench, a public benchmark for solving predictive tasks over relational databases with graph neural networks. RelBench provides databases and tasks spanning diverse do…

cs.LG2024★ 1 cited

PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning

Weihua Hu, Yiwen Yuan, Zecheng Zhang +6

We present PyTorch Frame, a PyTorch-based framework for deep learning over multi-modal tabular data. PyTorch Frame makes tabular deep learning easy by providing a PyTorch-based dat…