3 papers
cs.CV2026
DriftAD: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection
Wenyang Liu, Tianyi Liu, Dongshuo Zhang +2
Few-shot anomaly detection (FSAD) has recently benefited from vision-language models such as CLIP, which enable anomaly de?tection by aligning visual features with text description…
cs.AI2026
FADE: Mitigating Hallucinations by Reducing Language-Prior Dominance in Large Vision-Language Models
Yichen Guo, Kai Tang, Fenglai Lin +5
Despite the impressive capabilities of Large Vision-Language Models (LVLMs), they remain susceptible to hallucination, generating content inconsistent with the input image. Recent…
cs.RO2026
Spectral GS-SLAM: Observability-Aware, Degeneracy-Robust Tracking for Real-Time 3D Gaussian Splatting SLAM
Edward Beng Wai Tan, Siew-Kei Lam, Dongshuo Zhang
Recent 3DGS-SLAM systems enable real-time operation by leveraging conventional feature matching or ICP-based tracking, thereby avoiding the heavy dense photometric optimization use…