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 441–450 of 4891 papers

TitleStatusHype
InternVL-X: Advancing and Accelerating InternVL Series with Efficient Visual Token CompressionCode1
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
DiGRAF: Diffeomorphic Graph-Adaptive Activation FunctionCode1
JEN-1: Text-Guided Universal Music Generation with Omnidirectional Diffusion ModelsCode1
α-DPO: Adaptive Reward Margin is What Direct Preference Optimization NeedsCode1
KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series ForecastingCode1
DiRe-JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale DataCode1
Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellationCode1
Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical ImagingCode1
Differentially Flat Learning-based Model Predictive Control Using a Stability, State, and Input Constraining Safety FilterCode1
Show:102550
← PrevPage 45 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified