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 2261–2270 of 4891 papers

TitleStatusHype
GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-MeshCode2
Efficient Sound Field Reconstruction with Conditional Invertible Neural Networks—0
Adapting LLaMA Decoder to Vision TransformerCode1
Efficient Training of Probabilistic Neural Networks for Survival AnalysisCode0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
Bidirectional Long-Range Parser for Sequential Data Understanding—0
LHU-Net: A Light Hybrid U-Net for Cost-Efficient, High-Performance Volumetric Medical Image SegmentationCode2
GLCM-Based Feature Combination for Extraction Model Optimization in Object Detection Using Machine Learning—0
Unlocking Parameter-Efficient Fine-Tuning for Low-Resource Language Translation—0
Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection—0
Show:102550
← PrevPage 227 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified