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News/Anomaly-Preference Image Generation
arxiv
PublishedMay 5, 2026 at 4:00 AM
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Anomaly-Preference Image Generation

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arXiv:2605.02439v1 Announce Type: cross Abstract: Synthesizing realistic and diverse anomalous samples from limited data is vital for robust model generalization. However, existing methods struggle to reconcile fidelity and diversity, often hampered by distribution misalignment and overfitting, resp

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#anomaly-detection#machine-learning#computer-vision#generative-models

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Read original ↗All from arxiv →
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#anomaly-detection#machine-learning#computer-vision#generative-models

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