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Vietnamese-German University
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Achieving a staggering 95.41% mAP@10, FaLCon revolutionizes text-based person anomaly search by combining global semantic matching with fine-grained verification to tackle the Sim2Real challenge.
Geometry-aware inference can significantly enhance the stability of traffic predictions without the need for retraining existing models.
Semantic-F1 not only outperforms traditional metrics but also reveals critical insights into the reliability of automated fact-checking systems.
