This paper presents ArtiTwinSplat, a framework for constructing articulated, photo-realistic digital twins of objects directly from RGB-D videos in real-world environments.

This paper proposes the trans-domain digital twin approach to connect heterogeneous domain twins through aligned shared state, explicit coupling, heterogeneous temporal coordination, joint decision-ma…

This paper proposes a decentralized, blockchain-based protocol using both public and private blockchains to enhance the cyber resilience and security of IoT data transfer for digital building twins an…

The paper presents BoxTwin, an interactive digital twin framework that learns the full dynamics of elastoplastic articulated objects from videos and accurately tracks joint trajectories and reproduces…

This paper proposes a generative AI framework using a cGAN for proactive interference mitigation in ultra-dense indoor networks, achieving significant SINR gain, packet-loss reduction, and CSI oracle…

This paper proposes a Model-Based Systems Engineering workflow for creating Digital Twins of Renewable Energy Communities using SysML and the SAREF4ENER ontology.

The paper introduces i-SDT, an intelligent Self-Defending Digital Twin, which enhances cyber-physical security by accurately discriminating various attack types and maintaining safe operation without…

The paper introduces a threat-oriented digital twinning methodology to enable reproducible and controllable cybersecurity evaluation of autonomous platforms, overcoming limitations in accessing real-w…

The paper proposes a Digital Twin-enabled Simultaneous Learning and Modeling (DT-SLAM) framework to enhance secure communications in UAV-assisted networks against intelligent eavesdropping attacks, ac…

This paper proposes Twins, a unified continuous token space for multimodal models using ViT and VAE features, and addresses optimization imbalance with a focal regression objective.

The paper introduces DigitalCoach, a dataset of human expert-novice computer use coaching sessions, and evaluates the ability of state-of-the-art models to teach humans how to use computers.

The paper introduces AxDafny, a verifier-guided repair framework that improves verification success in Dafny by generating implementations, invariants, assertions, and termination arguments.

This paper proposes an arbiter for resolving conflicts between xApps in Open RAN by monitoring the fidelity of a network digital twin and switching between actions based on observed utility.

This paper presents a sustainable, low-cost Desktop Virtualization Infrastructure using discarded electronic equipment for digital education.

The paper introduces TECCI, a novel and challenging benchmark dataset of 7550 image-edit pairs, and demonstrates that current state-of-the-art text-guided image editing models struggle significantly w…

The paper demonstrates that off-the-shelf image diffusion models, like Stable Diffusion, can be repurposed to generate synthetic structured data, posing a threat of ground truth drift in closed eviden…

DEMUX is a novel framework that addresses the challenge of multi-tab website fingerprinting by treating the interleaved traffic as a demixing problem, achieving state-of-the-art performance in complex…

HySecTwin introduces a knowledge-driven digital twin framework that uses semantic modeling and hybrid reasoning to provide explainable, context-aware, and high-speed threat detection for complex Cyber…