17 citations · 18 across the 6 of their papers we have counts for
6 papers
CoCaRS: Correlation Calibration-Based Redundancy Suppression for Heterogeneous Knowledge Distillation
Fengming Yu, Haiwei Pan, Kejia Zhang +3
Knowledge distillation (KD) enables a compact student model to learn from a powerful teacher and has become an effective paradigm for model compression. The emergence of diverse mo…
STEAM: Stable Self-Training with Elastic Matching and Adaptive Purification
Shaoxiang Wang, Kejia Zhang, Haiwei Pan +2
Cross-view geo-localization (CVGL) aims to perform visual localization by matching drone-view images with corresponding satellite images. Existing supervised methods rely on large-…
Efficient Mathematical Reasoning Models via Dynamic Pruning and Knowledge Distillation
Fengming Yu, Qingyu Meng, Haiwei Pan +1
With the rapid development of deep learning, large language models have shown strong capabilities in complex reasoning tasks such as mathematical equation solving. However, their s…
UHKD: A Unified Framework for Heterogeneous Knowledge Distillation via Frequency-Domain Representations
Fengming Yu, Haiwei Pan, Kejia Zhang +2
Knowledge distillation (KD) is an effective model compression technique that transfers knowledge from a high-performance teacher to a lightweight student, reducing computational an…
CTS: A Consistency-Based Medical Image Segmentation Model
Kejia Zhang, Lan Zhang, Haiwei Pan +1
In medical image segmentation tasks, diffusion models have shown significant potential. However, mainstream diffusion models suffer from drawbacks such as multiple sampling times a…
MambaDFuse: A Mamba-based Dual-phase Model for Multi-modality Image Fusion
Zhe Li, Haiwei Pan, Kejia Zhang +2
Multi-modality image fusion (MMIF) aims to integrate complementary information from different modalities into a single fused image to represent the imaging scene and facilitate dow…