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 1421–1430 of 4891 papers

TitleStatusHype
LoRA Unlearns More and Retains More (Student Abstract)Code0
A Secure Estimator with Gaussian Bernoulli Mixture Model—0
STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing—0
DiffFNO: Diffusion Fourier Neural Operator—0
Y-MAP-Net: Real-time depth, normals, segmentation, multi-label captioning and 2D human pose in RGB images—0
Neural Graph Simulator for Complex Systems—0
The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases—0
When Mamba Meets xLSTM: An Efficient and Precise Method with the xLSTM-VMUNet Model for Skin lesion SegmentationCode0
Advancing Diffusion Models: Alias-Free Resampling and Enhanced Rotational Equivariance—0
Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature IntegrationCode1
Show:102550
← PrevPage 143 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified