17 citations · 17 across the 4 of their papers we have counts for
4 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…
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…
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…