3 papers
cs.LG2025
PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling
Yuxuan Yue, Zukang Xu, Zhihang Yuan +3
Large Language Models (LLMs) face significant challenges in edge deployment due to their massive parameter scale. Vector Quantization (VQ), a clustering-based quantization method,…
cs.LG2025
RWKVQuant: Quantizing the RWKV Family with Proxy Guided Hybrid of Scalar and Vector Quantization
Chen Xu, Yuxuan Yue, Zukang Xu +6
RWKV is a modern RNN architecture with comparable performance to Transformer, but still faces challenges when deployed to resource-constrained devices. Post Training Quantization (…
cs.LG2025
MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods
Zukang Xu, Yuxuan Yue, Xing Hu +7
Mamba is an efficient sequence model that rivals Transformers and demonstrates significant potential as a foundational architecture for various tasks. Quantization is commonly used…