most citedIGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research

37 citations · 37 across the 2 of their papers we have counts for

collaborators

2 papers

cs.IR2026

IRB: Automated Generation of Robust Factuality Benchmarks

Lam Thanh Do, Bhagyashree Taleka, Hozaifa Ammar Bhutta +3

Static benchmarks for RAG systems often suffer from rapid saturation and require significant manual effort to maintain robustness. To address this, we present IRB, a framework for…

cs.LG2023★ 37 cited

IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research

Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka +3

Graph neural networks (GNNs) have shown high potential for a variety of real-world, challenging applications, but one of the major obstacles in GNN research is the lack of large-sc…