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 2421–2430 of 4891 papers

TitleStatusHype
FViT: A Focal Vision Transformer with Gabor FilterCode1
Model Editing by Standard Fine-TuningCode1
Private PAC Learning May be Harder than Online Learning—0
Collaborative Learning with Different Labeling Functions—0
Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning—0
Multi-Fidelity Methods for Optimization: A Survey—0
Closed-form Filtering for Non-linear Systems—0
Exploiting Estimation Bias in Clipped Double Q-Learning for Continous Control Reinforcement Learning Tasks—0
Oracle-Efficient Differentially Private Learning with Public Data—0
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional SystemsCode0
Show:102550
← PrevPage 243 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified