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AnomalyJev: Towards Evaluating Image Anomaly Explanations via Claim-Level Verification
Recent multimodal LLM (MLLM)-based anomaly detection (AD) methods can generate textual explanations that help interpret their predictions. However, reliably and efficiently evaluating these explanations remains challenging. While LLM judges can assess explanations through structured rubrics, they of
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