185 citations · 191 across the 6 of their papers we have counts for
6 papers
Geometric Manifold Rectification for Imbalanced Learning
Xubin Wang, Qing Li, Weijia Jia
Imbalanced classification presents a formidable challenge in machine learning, particularly when tabular datasets are plagued by noise and overlapping class boundaries. From a geom…
Meta-Sel: Efficient Demonstration Selection for In-Context Learning via Supervised Meta-Learning
Xubin Wang, Weijia Jia
Demonstration selection is a practical bottleneck in in-context learning (ICL): under a tight prompt budget, accuracy can change substantially depending on which few-shot examples…
Empowering Edge Intelligence: A Comprehensive Survey on On-Device AI Models
Xubin Wang, Zhiqing Tang, Jianxiong Guo +4
The rapid advancement of artificial intelligence (AI) technologies has led to an increasing deployment of AI models on edge and terminal devices, driven by the proliferation of the…
Cognitive Edge Computing: A Comprehensive Survey on Optimizing Large Models and AI Agents for Pervasive Deployment
Xubin Wang, Qing Li, Weijia Jia
This article surveys Cognitive Edge Computing as a practical and methodical pathway for deploying reasoning-capable Large Language Models (LLMs) and autonomous AI agents on resourc…
Demonstration Selection for In-Context Learning via Reinforcement Learning
Xubin Wang, Jianfei Wu, Yichen Yuan +3
Diversity in demonstration selection is critical for enhancing model generalization by enabling broader coverage of structures and concepts. Constructing appropriate demonstration…
Enhancing Text Annotation through Rationale-Driven Collaborative Few-Shot Prompting
Jianfei Wu, Xubin Wang, Weijia Jia
The traditional data annotation process is often labor-intensive, time-consuming, and susceptible to human bias, which complicates the management of increasingly complex datasets.…