Ping Li

This paper demonstrates the successful application of deep learning-assisted differential fault attacks to three lightweight stream ciphers, achieving high fault location identification accuracies and reducing the overall attack complexity.

The paper introduces SEED, a large-scale benchmark dataset for tracing sequential deepfake facial edits, and proposes FAITH, a frequency-aware Transformer model that effectively detects and orders these cumulative editing events.

The paper introduces the Gaussian Privacy Protector (GPP), a framework that provides instance-level privacy for continuous data releases in federated learning by learning a stochastic encoder that sanitizes raw data while preserving utility.

The paper introduces Quantum Futures Interactive, a live, interdisciplinary demonstration platform designed to educate participants and facilitate dialogue on transitioning blockchain systems from classical to quantum-resilient security.

QSignAI is an open-source platform that integrates quantum-randomness-seeded identity signatures into a conversational AI social messaging system, demonstrating a practical bidirectional link between AI and quantum science.

This paper proposes a joint BERT-GNN architecture to systematically extract entities and relationships from diverse historical texts, achieving superior performance over conventional methods.

The paper proposes RPCASSM, a novel state space model leveraging Robust PCA (RPCA) to accurately detect and segment infrared small targets by separately modeling background and target information based on their unique spatial properties.

Omni-Flow is a distributed scheduling framework for multimodal inference that provides a unified abstraction for control flow, data flow, and compute flow.

This paper introduces the Kinematic-Aware Articulation Interface (KAI), a representation that captures the kinematic structure of articulated objects, improving sample efficiency and generalization in robot manipulation.