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 161–170 of 4891 papers

TitleStatusHype
Adaptive Multi-Scale Decomposition Framework for Time Series ForecastingCode2
Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence ModelingCode2
BEBLID: Boosted efficient binary local image descriptorCode2
L4acados: Learning-based models for acados, applied to Gaussian process-based predictive controlCode2
Accelerating Direct Preference Optimization with Prefix SharingCode2
GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-MeshCode2
FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow MatchingCode2
Learning local equivariant representations for quantum operatorsCode2
LeYOLO, New Scalable and Efficient CNN Architecture for Object DetectionCode2
Flow Matching in Latent SpaceCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified