most citedSIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation

3 citations · 3 across the 1 of their papers we have counts for

collaborators

5 papers

cs.DS2026

Near-Optimality for Single-Source Personalized PageRank

Xinpeng Jiang, Haoyu Liu, Siqiang Luo +1

The \emph{Single-Source Personalized PageRank} (SSPPR) query is central to graph OLAP, measuring the probability that an -decay random walk from node terminates a…

cs.LG20263 cited

SIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation

Haoyu Liu, Ningyi Liao, Siqiang Luo

Graph neural networks (GNNs) realize great success in graph learning but suffer from performance loss when meeting heterophily, i.e. neighboring nodes are dissimilar, due to their…

cs.CV2025

When Deepfake Detection Meets Graph Neural Network:a Unified and Lightweight Learning Framework

Haoyu Liu, Chaoyu Gong, Mengke He +3

The proliferation of generative video models has made detecting AI-generated and manipulated videos an urgent challenge. Existing detection approaches often fail to generalize acro…

cs.IR2025

Right Answer at the Right Time - Temporal Retrieval-Augmented Generation via Graph Summarization

Zulun Zhu, Haoyu Liu, Mengke He +1

Question answering in temporal knowledge graphs requires retrieval that is both time-consistent and efficient. Existing RAG methods are largely semantic and typically neglect expli…

cs.LG2025

A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness

Ningyi Liao, Haoyu Liu, Zulun Zhu +2

With recent advancements in graph neural networks (GNNs), spectral GNNs have received increasing popularity by virtue of their ability to retrieve graph signals in the spectral dom…