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20242026
most citedNext-Generation Phishing: How LLM Agents Empower Cyber Attackers

1 citations · 2 across the 12 of their papers we have counts for

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8 papers · 1 filter

cs.DC2024

Efficient Circuit Cutting and Scheduling in a Multi-Node Quantum System with Dynamic EPR Pairs

Zefan Du, Wenrui Zhang, Wenqi Wei +4

Despite advancements, current quantum hardware faces significant challenges, including limited qubit counts and high susceptibility to noise, which hinder the execution of large, c…

cs.DC2024

Hardware-aware Circuit Cutting and Distributed Qubit Mapping for Connected Quantum Systems

Zefan Du, Yanni Li, Zijian Mo +4

Quantum computing offers unparalleled computational capabilities but faces significant challenges, including limited qubit counts, diverse hardware topologies, and dynamic noise/er…

quant-ph2024

Circuit Folding: Scalable and Graph-Based Circuit Cutting via Modular Structure Exploitation

Shuwen Kan, Yanni Li, Hao Wang +2

Circuit cutting is a promising technique that leverages both quantum and classical computational resources, enabling the practical execution of large quantum circuits on noisy inte…

cs.CR2024★ 1 cited

Next-Generation Phishing: How LLM Agents Empower Cyber Attackers

Khalifa Afane, Wenqi Wei, Ying Mao +2

The escalating threat of phishing emails has become increasingly sophisticated with the rise of Large Language Models (LLMs). As attackers exploit LLMs to craft more convincing and…

cs.CR2024

Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning

Xueqing Zhang, Junkai Zhang, Ka-Ho Chow +6

This demo paper examines the susceptibility of Federated Learning (FL) systems to targeted data poisoning attacks, presenting a novel system for visualizing and mitigating such thr…

quant-ph2024

Scalable Circuit Cutting and Scheduling in a Resource-constrained and Distributed Quantum System

Shuwen Kan, Zefan Du, Miguel Palma +6

Despite quantum computing's rapid development, current systems remain limited in practical applications due to their limited qubit count and quality. Various technologies, such as…

quant-ph2024

Benchmarking Optimizers for Qumode State Preparation with Variational Quantum Algorithms

Shuwen Kan, Miguel Palma, Zefan Du +5

Quantum state preparation involves preparing a target state from an initial system, a process integral to applications such as quantum machine learning and solving systems of linea…

cs.DC2024

Resource-Efficient and Self-Adaptive Quantum Search in a Quantum-Classical Hybrid System

Zihao Jiang, Zefan Du, Shaolun Ruan +5

Over the past decade, the rapid advancement of deep learning and big data applications has been driven by vast datasets and high-performance computing systems. However, as we appro…