2 papers
cs.CV2026
EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models
Xiaomeng Peng, Xilang Huang, Seon Han Choi
Multimodal large language models (MLLMs) can enrich industrial anomaly detection with semantic descriptions and anomaly reasoning, but they still lag specialist anomaly detectors i…
cs.LG2025
Fast Re-Trainable Attention Autoencoder for Liquid Sensor Anomaly Detection at the Edge
Seongyun Choi
A lightweight, edge-deployable pipeline is proposed for detecting sensor anomalies in chemistry and biology laboratories. A custom PCB captures seven sensor channels and streams th…