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Pruning entire places instead of individual images can enhance dataset efficiency and model performance in visual place recognition by up to 3.5 times.
MG-RWKV achieves state-of-the-art TFL performance with a groundbreaking O(T) complexity, redefining efficiency in audio-visual content authenticity verification.
T2I models can now be diagnosed with unprecedented precision, linking defects directly to their semantic causes and importance for image quality.
