Author

Shang-Hang Zhang

h-index 11 View on Semantic Scholar

We have 3 of 27 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#artificial intelligence Preprint Sep 2026

STAR-Pro: Stage-Wise Token Adaptive Reduction with Progressive Refinement for Efficient Large Vision-Language Models

Large vision-language models (LVLMs) achieve strong multimodal understanding, but the hundreds to thousands of visual tokens they process impose substantial computational overhead, motivating training-free visual token pruning. In this work, we conduct two complementary analyses of visual token pruning. First, we measu...

Yi-Chen Guo, Tinghao Wang, Qizhe Zhang et al. · 0 citations

Jun 2026

FADE: Mitigating Hallucinations by Reducing Language-Prior Dominance in Large Vision-Language Models

This work proposes FADE (FFN Attenuation for DEcoding), a training-free method that attenuates FFN outputs to reduce language-prior dominance and shows that FADE effectively mitigates hallucinations while preserving inference efficiency.

Yichen Guo, Kai Tang, Fenglai Lin et al. · arXiv.org · 2 citations

Preprint Jul 2026

SeeMe: Mitigating Hallucinations in Large Vision-Language Models through Effective Visual Token Engineering

SeeMe is proposed, a training-free framework that introduces the concept of feature engineering from traditional machine learning into LVLMs and restructures visual tokens through a three-stage token engineering process to suppress hallucination sources while preserving informative visual evidence.

Kai Tang, Jinhao You, Bohua Zhang et al. · 2 citations