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Xiangyu Li

5 papers indexed

openalexScientific Reports2026-07-23

Performance evaluation of three multimodal large language models for pediatric profile-based orthodontic screening

Xiangyu Ge, Jingcheng Chen, Chenyang Yuan, Zhenghan Chu, Xiangyu Li, Xi Zhang, et al.

This study aimed to compare the performance of three multimodal large language models (ChatGPT, DeepSeek, and Gemini) in analyzing pediatric profile photographs and providing early orthodontic intervention recommendations, thereby assessing their clinical feasibility and reliabil…

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arxivcs.LGcs.AI2026-07-14

EMAGN: Efficient Multi-Attention Graph Network via Learned Clustering for Scalable Traffic Forecasting

Mingxing Xu, Rakesh Chowdary Machineni, Ke Liu, Xi Cheng, Chengqi Lu, Xin Hu, et al.

Traffic forecasting is highly challenging due to complex and nonlinear spatial and temporal dependencies. Self-attention mechanisms have been widely adopted to model dynamic and long-range dependencies, achieving state-of-the-art performance, but suffer from limited scalability d…

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arxivcs.CVcs.AI2026-07-03

MambaLIE: Scene Light Intensity-Boosted Low-Light Image Enhancement with State Space Model

Wanshu Fan, Xiangyu Li, Cong Wang, Kin-man Lam, Xin Yang, Haiyan Zhang, et al.

Images captured by consumer electronic devices, such as mobile phones and digital cameras, often suffer from low-light degradation due to sensor limitations and imaging pipelines, which degrades visual quality and affects downstream vision tasks. Existing methods based on Convolu…

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arxivcs.RO2026-06-28

Empowering a Single-Frequency GNSS Receiver to Achieve High-Precision Positioning with Relative Observations

Xingpeng Wang, Ziwen Qu, Juncheng Chen, Ruitian Pang, Xiangyu Li, Tiancheng Lai, et al.

Global Navigation Satellite System (GNSS) navigation is widely used to provide absolute, outdoor positioning in field robotics. Advances in Real-Time Kinematic (RTK) technology can achieve centimeter-level accuracy, facilitating autonomous navigation tasks. However, the cost and…

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crossrefMathematics2025-05-06Cited by 9

Multi-Domain Controversial Text Detection Based on a Machine Learning and Deep Learning Stacked Ensemble

Jiadi Liu, Zhuodong Liu, Qiaoqi Li, Weihao Kong, Xiangyu Li

Due to the rapid proliferation of social media and online reviews, the accurate identification and classification of controversial texts has emerged as a significant challenge in the field of natural language processing. However, traditional text-classification methodologies freq…

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