3 papers
cs.CV2026
Bidirectional Multimodal Prompt Learning with Scale-Aware Training for Few-Shot Multi-Class Anomaly Detection
Yujin Lee, Sewon Kim, Daeun Moon +2
Few-shot multi-class anomaly detection is crucial in real industrial settings, where only a few normal samples are available while numerous object types must be inspected. This set…
cs.CL2026
Being Kind Isn't Always Being Safe: Diagnosing Affective Hallucination in LLMs
Sewon Kim, Jiwon Kim, Seungwoo Shin +4
Large Language Models (LLMs) are increasingly engaged in emotionally vulnerable conversations that extend beyond information seeking to moments of personal distress. As they adopt…
cs.CV2025
LogicQA: Logical Anomaly Detection with Vision Language Model Generated Questions
Yejin Kwon, Daeun Moon, Youngje Oh +1
Anomaly Detection (AD) focuses on detecting samples that differ from the standard pattern, making it a vital tool in process control. Logical anomalies may appear visually normal y…