2 citations · 2 across the 3 of their papers we have counts for
3 papers · 1 filter
SubRot: Signed Gradient Subspace Calibration for VLM Rotation Quantization
Zhenhao Shang, Haizhao Jing, Haokui Zhang +4
Post-training quantization reduces the deployment cost of vision-language models (VLMs), but preserving multimodal capabilities at low bit widths remains challenging. Existing meth…
P4Q: Co-designing Token Pruning and Quantization for Vision-Language Model Acceleration
Haizhao Jing, Zhenhao Shang, Haokui Zhang +2
Vision language models have achieved strong performance across a wide range of multimodal applications, yet their substantial computational and memory costs hinder efficient deploy…
Rethinking Practical and Efficient Quantization Calibration for Vision-Language Models
Zhenhao Shang, Haizhao Jing, Guoting Wei +4
Post-training quantization (PTQ) is a primary approach for deploying large language models without fine-tuning, and the quantized performance is often strongly affected by the cali…