most citedLeveraging Vulnerabilities in Temporal Graph Neural Networks via Strategic High-Impact Assaults

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

collaborators

5 papers

cs.LG20251 cited

Leveraging Vulnerabilities in Temporal Graph Neural Networks via Strategic High-Impact Assaults

Dong Hyun Jeon, Lijing Zhu, Haifang Li +6

Temporal Graph Neural Networks (TGNNs) have become indispensable for analyzing dynamic graphs in critical applications such as social networks, communication systems, and financial…

cs.LG2025

DEM-NeRF: A Neuro-Symbolic Method for Scientific Discovery through Physics-Informed Simulation

Wenkai Tan, Alvaro Velasquez, Houbing Song

Neural networks have emerged as a powerful tool for modeling physical systems, offering the ability to learn complex representations from limited data while integrating foundationa…

cs.AI2025

SymRAG: Efficient Neuro-Symbolic Retrieval Through Adaptive Query Routing

Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +1

Current Retrieval-Augmented Generation systems use uniform processing, causing inefficiency as simple queries consume resources similar to complex multi-hop tasks. We present SymRA…

cs.CR2025

xIDS-EnsembleGuard: An Explainable Ensemble Learning-based Intrusion Detection System

Muhammad Adil, Mian Ahmad Jan, Safayat Bin Hakim +2

In this paper, we focus on addressing the challenges of detecting malicious attacks in networks by designing an advanced Explainable Intrusion Detection System (xIDS). The existing…

cs.LG2025

KGIF: Optimizing Relation-Aware Recommendations with Knowledge Graph Information Fusion

Dong Hyun Jeon, Wenbo Sun, Houbing Herbert Song +4

While deep-learning-enabled recommender systems demonstrate strong performance benchmarks, many struggle to adapt effectively in real-world environments due to limited use of user-…