116 citations · 360 across the 29 of their papers we have counts for
8 papers · 1 filter
DDTSE: Discriminative Diffusion Model for Target Speech Extraction
Leying Zhang, Yao Qian, Linfeng Yu +5
Diffusion models have gained attention in speech enhancement tasks, providing an alternative to conventional discriminative methods. However, research on target speech extraction u…
Liquid Metal Molecular Scissors
Liangfei Duan, Tong Zhou, Huiqin Yang +4
Molecules are the smallest unit in matters that can exist independently, relatively stable, and maintain physical and chemical activities. The atomic species, alignment commands, a…
Knowledge-Driven Resource Allocation for D2D Networks: A WMMSE Unrolled Graph Neural Network Approach
Hao Yang, Nan Cheng, Ruijin Sun +5
This paper proposes an novel knowledge-driven approach for resource allocation in device-to-device (D2D) networks using a graph neural network (GNN) architecture. To meet the milli…
Few-shot Class-incremental Learning for Cross-domain Disease Classification
Hao Yang, Weijian Huang, Jiarun Liu +2
The ability to incrementally learn new classes from limited samples is crucial to the development of artificial intelligence systems for real clinical application. Although existin…
MGA: Medical generalist agent through text-guided knowledge transformation
Weijian Huang, Hao Yang, Cheng Li +3
Multi-modal representation methods have achieved advanced performance in medical applications by extracting more robust features from multi-domain data. However, existing methods u…
Predicted Embedding Power Regression for Large-Scale Out-of-Distribution Detection
Hong Yang, William Gebhardt, Alexander G. Ororbia +1
Out-of-distribution (OOD) inputs can compromise the performance and safety of real world machine learning systems. While many methods exist for OOD detection and work well on small…
Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness
Zahra Ashktorab, Benjamin Hoover, Mayank Agarwal +4
Mitigating algorithmic bias is a critical task in the development and deployment of machine learning models. While several toolkits exist to aid machine learning practitioners in a…
SwiftAvatar: Efficient Auto-Creation of Parameterized Stylized Character on Arbitrary Avatar Engines
Shizun Wang, Weihong Zeng, Xu Wang +7
The creation of a parameterized stylized character involves careful selection of numerous parameters, also known as the "avatar vectors" that can be interpreted by the avatar engin…