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Improving and Assessing Anomaly Detectors for Large-Scale Settings
We conduct extensive experiments in these more realistic settings for out-of-distribution detection and find that a surprisingly simple detector based on the maximum logit outperforms prior methods in all the large-scale multi-class, multi-label, and segmentation tasks, establishing a simple new baseline for future work.
Lift-the-flap: what, where and when for context reasoning
Context reasoning is critical in a wide variety of applications where current inputs need to be interpreted in the light of previous experience and knowledge.
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