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cs.LG2026
Why Does Post-Training Quantization Work?
Yuxiang Chen, Michael Beyer, Jun Zhu +1
Post-training quantization compresses large language models (LLMs) by storing their weights at reduced precision, and each quantized weight introduces an error into the hidden stat…
cs.CV2026
Efficient Difficulty-Aware Dynamic Routing for Diffusion-Based Real-World Image Super-Resolution
Xue Wu, Kang Zhao, Kafeng Wang +4
Diffusion-based methods have achieved impressive performance in real-world image super-resolution (Real-ISR) by leveraging large pre-trained stable diffusion (SD) models as powerfu…