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 481–490 of 4891 papers

TitleStatusHype
Hyper-CL: Conditioning Sentence Representations with HypernetworksCode1
Efficient and Accurate Pneumonia Detection Using a Novel Multi-Scale Transformer ApproachCode1
EdgeRegNet: Edge Feature-based Multimodal Registration Network between Images and LiDAR Point CloudsCode1
MobileIQA: Exploiting Mobile-level Diverse Opinion Network For No-Reference Image Quality Assessment Using Knowledge DistillationCode1
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PCCode1
Model Editing by Standard Fine-TuningCode1
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent CodingCode1
Ferret: Federated Full-Parameter Tuning at Scale for Large Language ModelsCode1
FedPop: Federated Population-based Hyperparameter TuningCode1
Federated Bayesian Optimization via Thompson SamplingCode1
Show:102550
← PrevPage 49 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified