3 papers
cs.CV2026
Are Reasoning Vision-Language Models Robust to Semantic Visual Distractions?
Yizheng Sun, Mochuan Zhan, Yanan Ma +10
Reasoning Vision-Language Models (VLMs) achieve strong performance on complex multimodal tasks, but reliable real-world application requires handling visual inputs that are messier…
cs.CV2025
Does Acceleration Cause Hidden Instability in Vision Language Models? Uncovering Instance-Level Divergence Through a Large-Scale Empirical Study
Yizheng Sun, Hao Li, Chang Xu +4
Vision-Language Models (VLMs) are powerful yet computationally intensive for widespread practical deployments. To address such challenge without costly re-training, post-training a…
cs.CL2025
LVPruning: An Effective yet Simple Language-Guided Vision Token Pruning Approach for Multi-modal Large Language Models
Yizheng Sun, Yanze Xin, Hao Li +3
Multi-modal Large Language Models (MLLMs) have achieved remarkable success by integrating visual and textual modalities. However, they incur significant computational overhead due…