3 papers
cs.LG2025
OTARo: Once Tuning for All Precisions toward Robust On-Device LLMs
Shaoyuan Chen, Zhixuan Chen, Dawei Yang +2
Large Language Models (LLMs) fine-tuning techniques not only improve the adaptability to diverse downstream tasks, but also mitigate adverse effects of model quantization. Despite…
cs.CV2025
VAEVQ: Enhancing Discrete Visual Tokenization through Variational Modeling
Sicheng Yang, Xing Hu, Qiang Wu +1
Vector quantization (VQ) transforms continuous image features into discrete representations, providing compressed, tokenized inputs for generative models. However, VQ-based framewo…
cs.LG2025
RSAVQ: Riemannian Sensitivity-Aware Vector Quantization for Large Language Models
Zukang Xu, Xing Hu, Qiang Wu +1
Large language models (LLMs) have demonstrated remarkable performance across a wide range of natural language processing tasks. However, their exponentially increasing parameters p…