Qing Zhang

The paper proposes a channel prediction-based Physical Layer Authentication (PLA) framework using a Transformer module to maintain robust authentication accuracy against consecutive spoofing attacks in wireless networks.

LibScan is an automated framework that detects eight categories of smart contract library misuse by combining LLM-based semantic reasoning with rule-based analysis, achieving 85.15% accuracy on real-world contracts.

AccLock proposes a passive, zero-involvement user authentication system that uses unique biometric features from in-ear accelerometers (BCG signals) to achieve secure and unobtrusive identity verification.

This paper develops a unified spectral analysis framework to explain how knowledge transfer (KT) works across different machine learning regimes, such as Knowledge Distillation and Weak-to-Strong generalization.

This paper introduces Repeated Policy Regret (RP-Regret), a novel game-theoretic metric for analyzing regret in repeated games with adaptive opponents, and proposes algorithms to minimize it.

This paper introduces AUTOGATE, an agentic framework for industry-grade RTL power optimization using ML-LLM co-design and hierarchical multi-agent architecture.

This paper conducts a longitudinal study on Android app signing credentials leakage, identifying over 5,600 compromised keystores and 278 affected apps.

DigenRL is a disaggregated RL framework for diffusion-based generative LLMs that achieves 1.56-2.10x throughput improvements over state-of-the-art diffusion RL systems.