4 papers
Displacement Preserving Relational Distillation for Robust Medical Segmentation
Zhicheng Ding, Xinyu Chu, Jung Im Choi +5
Accurate 3D medical segmentation is limited by anatomical variability and high computational costs. While knowledge distillation (KD) offers a route for model compression, conventi…
SWARD: Stochastic Window-Attention-Based Relational Distillation for Cross-Architectural Semantic Segmentation
Aditya Makineni, Qing Tian
Large-scale vision foundation models have driven substantial gains on dense prediction tasks such as semantic segmentation, but their size makes deployment impractical in resource-…
Learnable Instance Attention Filtering for Adaptive Detector Distillation
Chen Liu, Qizhen Lan, Zhicheng Ding +2
As deep vision models grow increasingly complex to achieve higher performance, deployment efficiency has become a critical concern. Knowledge distillation (KD) mitigates this issue…
ETT-CKGE: Efficient Task-driven Tokens for Continual Knowledge Graph Embedding
Lijing Zhu, Qizhen Lan, Qing Tian +8
Continual Knowledge Graph Embedding (CKGE) seeks to integrate new knowledge while preserving past information. However, existing methods struggle with efficiency and scalability du…