most citedDigital Twin AI: Opportunities and Challenges from Large Language Models to World Models

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.AI2026

From Event Logs to Governed Action: A BlueSky Agenda for Agentic Process Mining

Yiyuan Yang, Zheshun Wu, Yong Chu +3

Process mining has long turned event logs into process knowledge: discovered models, conformance evidence, bottleneck diagnoses, and runtime predictions. Agentic AI changes the tar…

eess.SP2026

M3F-UAV: A Missing-Modality Multimodal Foundation Model for Low-Altitude Wireless Sensing

Pengxuan Gao, Kai Ying, Botao Wu +2

Low-altitude unmanned aerial vehicles (UAVs) are emerging as key platforms for wireless intelligence tasks. However, practical low-altitude wireless systems usually operate in comp…

cs.HC2026

From Memorization to Creation: Evaluating the Cognitive Depth of LLM-Generated Educational Questions

Xiaolong Wang, Zhe Zhao, Song Lai +5

While LLMs show promise in automating educational content creation, their ability to generate questions that stimulate higher-order thinking remains understudied. This work evaluat…

cs.AI20261 cited

Digital Twin AI: Opportunities and Challenges from Large Language Models to World Models

Rong Zhou, Dongping Chen, Zihan Jia +24

Digital twins, as precise digital representations of physical systems, have evolved from passive simulation tools into intelligent and autonomous entities through the integration o…

cs.LG2024

Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting

Tianxiang Zhan, Yuanpeng He, Yong Deng +3

In practical scenarios, time series forecasting necessitates not only accuracy but also efficiency. Consequently, the exploration of model architectures remains a perennially trend…

cs.LG2024

DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series

Zahra Zamanzadeh Darban, Yiyuan Yang, Geoffrey I. Webb +4

In time series anomaly detection (TSAD), the scarcity of labeled data poses a challenge to the development of accurate models. Unsupervised domain adaptation (UDA) offers a solutio…