3 papers
cs.CV2026
Diagnosing and Repairing Unsafe Channels in Vision-Language Models via Causal Discovery and Dual-Modal Safety Subspace Projection
Jinhu Fu, Yihang Lou, Qingyi Si +3
Large Vision-Language Models (LVLMs) have achieved impressive performance across multimodal understanding and reasoning tasks, yet their internal safety mechanisms remain opaque an…
cs.LG2026
Residual Stream Analysis of Overfitting And Structural Disruptions
Quan Liu, Han Zhou, Wenquan Wu +2
Ensuring that large language models (LLMs) remain both helpful and harmless poses a significant challenge: fine-tuning on repetitive safety datasets, where unsafe prompts are paire…
cs.CV2025
Mitigating Group-Level Fairness Disparities in Federated Visual Language Models
Chaomeng Chen, Zitong Yu, Junhao Dong +4
Visual language models (VLMs) have shown remarkable capabilities in multimodal tasks but face challenges in maintaining fairness across demographic groups, particularly when deploy…