6 citations · 16 across the 23 of their papers we have counts for
8 papers · 1 filter
AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality
Peijun Qing, Chongyang Gao, Yefan Zhou +3
Parameter-efficient fine-tuning methods, such as Low-Rank Adaptation (LoRA), are known to enhance training efficiency in Large Language Models (LLMs). Due to the limited parameters…
Learning Spatial-Preserving Hierarchical Representations for Digital Pathology
Weiyi Wu, Xingjian Diao, Chunhui Zhang +4
Whole slide images (WSIs) pose fundamental computational challenges due to their gigapixel resolution and the sparse distribution of informative regions. Existing approaches often…
Judging the Judges: A Systematic Study of Position Bias in LLM-as-a-Judge
Lin Shi, Chiyu Ma, Wenhua Liang +3
LLM-as-a-Judge has emerged as a promising alternative to human evaluators across various tasks, yet inherent biases - particularly position bias, the tendency to favor solutions ba…
GluMarker: A Novel Predictive Modeling of Glycemic Control Through Digital Biomarkers
Ziyi Zhou, Ming Cheng, Xingjian Diao +2
The escalating prevalence of diabetes globally underscores the need for diabetes management. Recent research highlights the growing focus on digital biomarkers in diabetes manageme…
Toward Short-Term Glucose Prediction Solely Based on CGM Time Series
Ming Cheng, Xingjian Diao, Ziyi Zhou +3
The global diabetes epidemic highlights the importance of maintaining good glycemic control. Glucose prediction is a fundamental aspect of diabetes management, facilitating real-ti…
CrossGP: Cross-Day Glucose Prediction Excluding Physiological Information
Ziyi Zhou, Ming Cheng, Yanjun Cui +2
The increasing number of diabetic patients is a serious issue in society today, which has significant negative impacts on people's health and the country's financial expenditures.…
Efflex: Efficient and Flexible Pipeline for Spatio-Temporal Trajectory Graph Modeling and Representation Learning
Ming Cheng, Ziyi Zhou, Bowen Zhang +7
In the landscape of spatio-temporal data analytics, effective trajectory representation learning is paramount. To bridge the gap of learning accurate representations with efficient…
VeTraSS: Vehicle Trajectory Similarity Search Through Graph Modeling and Representation Learning
Ming Cheng, Bowen Zhang, Ziyu Wang +4
Trajectory similarity search plays an essential role in autonomous driving, as it enables vehicles to analyze the information and characteristics of different trajectories to make…