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 961–970 of 4891 papers

TitleStatusHype
Target Localization with Coprime Multistatic MIMO Radar via Coupled Canonical Polyadic Decomposition Based on Joint Eigenvalue Decomposition—0
CPINN-ABPI: Physics-Informed Neural Networks for Accurate Power Estimation in MPSoCs—0
Dissecting Physics Reasoning in Small Language Models: A Multi-Dimensional Analysis from an Educational Perspective—0
A False Discovery Rate Control Method Using a Fully Connected Hidden Markov Random Field for Neuroimaging DataCode0
ZigzagPointMamba: Spatial-Semantic Mamba for Point Cloud Understanding—0
Leveraging Diffusion Models for Parameterized Quantum Circuit Generation—0
Visual Loop Closure Detection Through Deep Graph Consensus—0
Long-Context State-Space Video World Models—0
Graph Guided Diffusion: Unified Guidance for Conditional Graph Generation—0
CaseEdit: Enhancing Localized Commonsense Reasoning via Null-Space Constrained Knowledge Editing in Small Parameter Language Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified