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 1151–1160 of 4891 papers

TitleStatusHype
Semantic-guided Cross-Modal Prompt Learning for Skeleton-based Zero-shot Action Recognition—0
Dynamic Group Normalization: Spatio-Temporal Adaptation to Evolving Data Statistics—0
Dataset Distillation with Neural Characteristic Function: A Minmax PerspectiveCode3
SuperLightNet: Lightweight Parameter Aggregation Network for Multimodal Brain Tumor SegmentationCode0
Star with Bilinear Mapping—0
DefMamba: Deformable Visual State Space Model—0
VISTREAM: Improving Computation Efficiency of Visual Streaming Perception via Law-of-Charge-Conservation Inspired Spiking Neural Network—0
RivuletMLP: An MLP-based Architecture for Efficient Compressed Video Quality Enhancement—0
STEPS: Sequential Probability Tensor Estimation for Text-to-Image Hard Prompt Search—0
Learning Weather Models from Data with WSINDy—0
Show:102550
← PrevPage 116 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified