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

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Showing 1081–1090 of 4891 papers

TitleStatusHype
Design and Experimental Test of Datatic Approximate Optimal Filter in Nonlinear Dynamic Systems—0
Video Dataset Condensation with Diffusion Models—0
Improving Generalization of Medical Image Registration Foundation ModelCode0
Probing In-Context Learning: Impact of Task Complexity and Model Architecture on Generalization and EfficiencyCode0
OptiGait-LGBM: An Efficient Approach of Gait-based Person Re-identification in Non-Overlapping Regions—0
Generative Discovery of Partial Differential Equations by Learning from Math Handbooks—0
Auto Tensor Singular Value Thresholding: A Non-Iterative and Rank-Free Framework for Tensor Denoising—0
A High-Dimensional Feature Selection Algorithm Based on Multiobjective Differential Evolution—0
Assessing Tenstorrent's RISC-V MatMul Acceleration Capabilities—0
Integrating Building Thermal Flexibility Into Distribution System: A Privacy-Preserved Dispatch Approach—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified