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Image-based Outlier Synthesis With Training Data

arXiv — cs.LG•Friday, November 14, 2025 at 5:00:00 AM
NeutralArtificial Intelligence
The study on OOD detection highlights a significant gap in current research, which often focuses on conventional cases. This aligns with findings in related works like 'EnchTable,' which emphasizes the importance of fine-tuning large language models for specialized tasks, and 'TubeRMC,' which addresses complex spatio-temporal challenges. Both articles underline the necessity for innovative approaches in machine learning that can adapt to nuanced scenarios without external data reliance. The proposed ASCOOD framework aims to bridge this gap by synthesizing virtual outliers, enhancing the robustness of deep learning applications in critical domains.
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