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 1261–1270 of 4891 papers

TitleStatusHype
RWKV-Lite: Deeply Compressed RWKV for Resource-Constrained Devices—0
A Diagrammatic Approach to Improve Computational Efficiency in Group Equivariant Neural Networks—0
Pretrained Event Classification Model for High Energy Physics Analysis—0
Rethinking Chain-of-Thought from the Perspective of Self-TrainingCode1
Audio-based Anomaly Detection in Industrial Machines Using Deep One-Class Support Vector Data Description—0
Enhancing Off-Grid One-Bit DOA Estimation with Learning-Based Sparse Bayesian Approach for Non-Uniform Sparse Array—0
Reliable and superior elliptic Fourier descriptor normalization and its application software ElliShape with efficient image processing—0
Evaluating the effectiveness, reliability and efficiency of a multi-objective sequential optimization approach for building performance design—0
FM2S: Towards Spatially-Correlated Noise Modeling in Zero-Shot Fluorescence Microscopy Image DenoisingCode1
Optimal Bounds for Private Minimum Spanning Trees via Input Perturbation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified