2 papers
cs.CV2025
Efficient Vision-Language Reasoning via Adaptive Token Pruning
Xue Li, Xiaonan Song, Henry Hu
Real-world deployment of Vision-Language Models (VLMs) is hindered by high computational demands, as existing architectures inefficiently process all tokens uniformly. We introduce…
cs.LG2024
MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design
Zhen Zheng, Xiaonan Song, Chuanjie Liu
Quantization has become one of the most effective methodologies to compress LLMs into smaller size. However, the existing quantization solutions still show limitations of either no…