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cs.CV2025
Hierarchical Feature-level Reverse Propagation for Post-Training Neural Networks
Ni Ding, Shuchang Wang, Lei He +2
End-to-end neural networks have become a dominant paradigm in autonomous driving, where reliable deployment requires controllable post-training adaptation and improved transparency…
cs.CV2025
Post-Training Quantization for Diffusion Transformer via Hierarchical Timestep Grouping
Ning Ding, Jing Han, Yuchuan Tian +3
Diffusion Transformer (DiT) has now become the preferred choice for building image generation models due to its great generation capability. Unlike previous convolution-based UNet…