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 171–180 of 4891 papers

TitleStatusHype
Retinexmamba: Retinex-based Mamba for Low-light Image EnhancementCode2
On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?Code2
SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image DenoisingCode2
Latent Modulated Function for Computational Optimal Continuous Image RepresentationCode2
MultiBooth: Towards Generating All Your Concepts in an Image from TextCode2
Partial Large Kernel CNNs for Efficient Super-ResolutionCode2
Rethinking Transformer-Based Blind-Spot Network for Self-Supervised Image DenoisingCode2
GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-MeshCode2
LHU-Net: A Light Hybrid U-Net for Cost-Efficient, High-Performance Volumetric Medical Image SegmentationCode2
Grappa -- A Machine Learned Molecular Mechanics Force FieldCode2
Show:102550
← PrevPage 18 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified