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cs.CV2026

Anti-Shortcut Distillation via Temporal Negative Knowledge Transfer

Syed Muhammad Raza, Omer Tariq, Jeongbae Son

Knowledge distillation (KD) trains a compact student by attracting it towards a converged teacher. It is silent about which directions the teacher itself learned to suppress: repul…

cs.CV2026

ProCache: Constraint-Aware Feature Caching with Selective Computation for Diffusion Transformer Acceleration

Fanpu Cao, Yaofo Chen, Zeng You +1

Diffusion Transformers (DiTs) have achieved state-of-the-art performance in generative modeling, yet their high computational cost hinders real-time deployment. While feature cachi…

cs.CV2025

Sensitivity-Aware Post-Training Quantization for Deep Neural Networks

Zekang Zheng, Haokun Li, Yaofo Chen +2

Model quantization reduces neural network parameter precision to achieve compression, but often compromises accuracy. Existing post-training quantization (PTQ) methods employ itera…

cs.CV2024

Towards Long Video Understanding via Fine-detailed Video Story Generation

Zeng You, Zhiquan Wen, Yaofo Chen +4

Long video understanding has become a critical task in computer vision, driving advancements across numerous applications from surveillance to content retrieval. Existing video und…

cs.CV2024

Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation

Yaofo Chen, Shuaicheng Niu, Yaowei Wang +3

The conventional deep learning paradigm often involves training a deep model on a server and then deploying the model or its distilled ones to resource-limited edge devices. Usuall…

cs.CV2024

Automated Dominative Subspace Mining for Efficient Neural Architecture Search

Yaofo Chen, Yong Guo, Daihai Liao +4

Neural Architecture Search (NAS) aims to automatically find effective architectures within a predefined search space. However, the search space is often extremely large. As a resul…