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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 161–170 of 4891 papers

TitleStatusHype
Neural Network-based Information-Theoretic Transceivers for High-Order Modulation Schemes—0
Latent Wavelet Diffusion: Enabling 4K Image Synthesis for Free—0
Learning to Upsample and Upmix Audio in the Latent Domain—0
The Security Threat of Compressed Projectors in Large Vision-Language Models—0
Geo-Sign: Hyperbolic Contrastive Regularisation for Geometrically Aware Sign Language TranslationCode1
Efficient RAW Image Deblurring with Adaptive Frequency ModulationCode1
Edge Computing for Physics-Driven AI in Computational MRI: A Feasibility Study—0
Pretraining Deformable Image Registration Networks with Random ImagesCode0
TumorGen: Boundary-Aware Tumor-Mask Synthesis with Rectified Flow Matching—0
K^2IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson ProcessesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified