A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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Introduces Correlated Low-Rank Adaptation (CoLoRA), a novel framework that explicitly models correlations among low-rank factors to improve parameter-efficient fine-tuning of convolutional networks.
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ConvNets (NFNets) match Vision Transformers in performance when pre-trained on large datasets and fine-tuned on ImageNet, challenging the assumption that ViTs are inherently superior at scale.
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LeViT is a hybrid vision transformer optimized for fast inference, achieving superior speed-accuracy tradeoffs over convnets and ViTs.