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 1051–1060 of 4891 papers

TitleStatusHype
An Integrated Artificial Intelligence Operating System for Advanced Low-Altitude Aviation Applications—0
ACL: Activating Capability of Linear Attention for Image Restoration—0
Client Selection Strategies for Federated Semantic Communications in Heterogeneous IoT Networks—0
An Integer Polynomial Programming Based Framework for Lifted MAP Inference—0
An Integer Clustering Approach for Modeling Large-Scale EV Fleets with Guaranteed Performance—0
Class-relevant Patch Embedding Selection for Few-Shot Image Classification—0
A Diagrammatic Approach to Improve Computational Efficiency in Group Equivariant Neural Networks—0
Doubly Stochastic Adaptive Neighbors Clustering via the Marcus Mapping—0
DefMamba: Deformable Visual State Space Model—0
Classification of residential and non-residential buildings based on satellite data using deep learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified