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XPose: eXplainable Human Pose Estimation
In this paper, we propose XPose, a novel framework that incorporates Explainable AI (XAI) principles into pose estimation.
On Leveraging Large Language Models for Enhancing Entity Resolution: A Cost-efficient Approach
Entity resolution, the task of identifying and merging records that refer to the same real-world entity, is crucial in sectors like e-commerce, healthcare, and law enforcement.
HMSG: Heterogeneous Graph Neural Network based on Metapath Subgraph Learning
Based on these observations, we propose a new heterogeneous graph neural network model named HMSG to comprehensively capture structural, semantic and attribute information from both homogeneous and heterogeneous neighbors.
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