collaborators

5 papers

quant-ph2026

Experimental robustness benchmarking of quantum neural networks on a superconducting quantum processor

Hai-Feng Zhang, Zhao-Yun Chen, Peng Wang +17

Quantum machine learning (QML) models, like their classical counterparts, are vulnerable to adversarial attacks, hindering their secure deployment. Here, we report the first system…

cs.LG2025

Black-Box Auditing of Quantum Model: Lifted Differential Privacy with Quantum Canaries

Baobao Song, Shiva Raj Pokhrel, Athanasios V. Vasilakos +2

Quantum machine learning (QML) promises significant computational advantages, yet models trained on sensitive data risk memorizing individual records, creating serious privacy vuln…

cs.RO2025

Neural Brain: A Neuroscience-inspired Framework for Embodied Agents

Jian Liu, Xiongtao Shi, Thai Duy Nguyen +13

The rapid evolution of artificial intelligence (AI) has shifted from static, data-driven models to dynamic systems capable of perceiving and interacting with real-world environment…

cs.CL2025

Breaking BERT: Gradient Attack on Twitter Sentiment Analysis for Targeted Misclassification

Akil Raj Subedi, Taniya Shah, Aswani Kumar Cherukuri +1

Social media platforms like Twitter have increasingly relied on Natural Language Processing NLP techniques to analyze and understand the sentiments expressed in the user generated…

quant-ph2025

Towards A Hybrid Quantum Differential Privacy

Baobao Song, Shiva Raj Pokhrel, Athanasios V. Vasilakos +2

Quantum computing offers unparalleled processing power but raises significant data privacy challenges. Quantum Differential Privacy (QDP) leverages inherent quantum noise to safegu…