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 341–350 of 4891 papers

TitleStatusHype
NeRF and Gaussian Splatting SLAM in the WildCode1
Gracefully Filtering Backdoor Samples for Generative Large Language Models without RetrainingCode1
How Much Can Time-related Features Enhance Time Series Forecasting?Code1
Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging DatasetsCode1
VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics PredictionCode1
LDM-Morph: Latent diffusion model guided deformable image registrationCode1
Recursive Gaussian Process State Space ModelCode1
Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature IntegrationCode1
Large-scale moral machine experiment on large language modelsCode1
LSSInst: Improving Geometric Modeling in LSS-Based BEV Perception with Instance RepresentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified