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20242026
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★ 1 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.AI2025

GeoBS: Information-Theoretic Quantification of Geographic Bias in AI Models

Zhangyu Wang, Nemin Wu, Qian Cao +8

The widespread adoption of AI models, especially foundation models (FMs), has made a profound impact on numerous domains. However, it also raises significant ethical concerns, incl…

cs.CV2025

4KAgent: Agentic Any Image to 4K Super-Resolution

Yushen Zuo, Qi Zheng, Mingyang Wu +10

We present 4KAgent, a unified agentic super-resolution generalist system designed to universally upscale any image to 4K resolution (and even higher, if applied iteratively). Our s…

cs.CV2025

LocDiff: Identifying Locations on Earth by Diffusing in the Hilbert Space

Zhangyu Wang, Zeping Liu, Jielu Zhang +8

Image geolocalization is a fundamental yet challenging task, aiming at inferring the geolocation on Earth where an image is taken. State-of-the-art methods employ either grid-based…

cs.CV2025

GAIR: Location-Aware Self-Supervised Contrastive Pre-Training with Geo-Aligned Implicit Representations

Zeping Liu, Ni Lao, Zhangyu Wang +2

Vision Transformer (ViT) has been widely used in computer vision tasks with excellent results by providing representations for a whole image or image patches. However, ViT lacks de…

cs.LG2024

LLM-Mixer: Multiscale Mixing in LLMs for Time Series Forecasting

Md Kowsher, Md. Shohanur Islam Sobuj, Nusrat Jahan Prottasha +3

Time series forecasting remains a challenging task, particularly in the context of complex multiscale temporal patterns. This study presents LLM-Mixer, a framework that improves fo…

cs.CV2024

Examining the Commitments and Difficulties Inherent in Multimodal Foundation Models for Street View Imagery

Zhenyuan Yang, Xuhui Lin, Qinyi He +10

The emergence of Large Language Models (LLMs) and multimodal foundation models (FMs) has generated heightened interest in their applications that integrate vision and language. Thi…