SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 361–370 of 4891 papers

TitleStatusHype
Dynamic Cardiac MRI Reconstruction Using Combined Tensor Nuclear Norm and Casorati Matrix Nuclear Norm RegularizationsCode1
Estimating Koopman operators with sketching to provably learn large scale dynamical systemsCode1
Rethinking Brain Tumor Segmentation from the Frequency Domain PerspectiveCode1
Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated UncertaintyCode1
Adaptive Focus for Efficient Video RecognitionCode1
EViT: An Eagle Vision Transformer with Bi-Fovea Self-AttentionCode1
Dynamic Clustering and Cluster Contrastive Learning for Unsupervised Person Re-identificationCode1
ExpoMamba: Exploiting Frequency SSM Blocks for Efficient and Effective Image EnhancementCode1
Adaptive Fourier Neural Operators: Efficient Token Mixers for TransformersCode1
Dual Prototype Evolving for Test-Time Generalization of Vision-Language ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified