most citedA Survey on Graph Condensation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IR2025

DPDisc: From Factoid Questions to Data Product Requests for Open-World Data Product Discovery over Tables and Text

Liangliang Zhang, Nandana Mihindukulasooriya, Niharika S. D'Souza +4

Data products are reusable, self-contained assets designed for specific business use cases. Automating their discovery is of great industry interest, as it enables efficient data a…

cs.CL2025

Diagnosing and Addressing Pitfalls in KG-RAG Datasets: Toward More Reliable Benchmarking

Liangliang Zhang, Zhuorui Jiang, Hongliang Chi +8

Knowledge Graph Question Answering (KGQA) systems rely on high-quality benchmarks to evaluate complex multi-hop reasoning. However, despite their widespread use, popular datasets s…

cs.LG2024

Extending Graph Condensation to Multi-Label Datasets: A Benchmark Study

Liangliang Zhang, Haoran Bao, Yao Ma

As graph data grows increasingly complicate, training graph neural networks (GNNs) on large-scale datasets presents significant challenges, including computational resource constra…

cs.LG2024★ 1 cited

A Survey on Graph Condensation

Hongjia Xu, Liangliang Zhang, Yao Ma +3

Analytics on large-scale graphs have posed significant challenges to computational efficiency and resource requirements. Recently, Graph condensation (GC) has emerged as a solution…

cs.CY2024

A Survey on Safe Multi-Modal Learning System

Tianyi Zhao, Liangliang Zhang, Yao Ma +1

In the rapidly evolving landscape of artificial intelligence, multimodal learning systems (MMLS) have gained traction for their ability to process and integrate information from di…