4 papers
The Geometry Behind Diffusion and Flow Matching: Gradient Flows and Geodesics in Wasserstein Space
Yian Yao, Weiwei Zhang
The space ) of probability measures with finite second moment carries a natural geometry: the quadratic Wasserstein distance W_2 makes it a complete met…
SignRoundV2: Toward Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs
Wenhua Cheng, Weiwei Zhang, Heng Guo +2
Extremely low-bit quantization is critical for efficiently deploying Large Language Models (LLMs), yet it often leads to severe performance degradation at 2 bits and even at 4 bits…
Effective Quantization for Diffusion Models on CPUs
Hanwen Chang, Haihao Shen, Yiyang Cai +7
Diffusion models have gained popularity for generating images from textual descriptions. Nonetheless, the substantial need for computational resources continues to present a notewo…
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
Wenhua Cheng, Weiwei Zhang, Haihao Shen +4
Large Language Models (LLMs) have demonstrated exceptional proficiency in language-related tasks, but their deployment poses significant challenges due to substantial memory and st…