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 2921–2930 of 4891 papers

TitleStatusHype
Supervised Learning in Automatic Channel Selection for Epileptic Seizure Detection—0
Support estimation in high-dimensional heteroscedastic mean regression—0
SUPRA: Subspace Parameterized Attention for Neural Operator on General Domains—0
Surrogate Assisted Evolutionary Multi-objective Optimisation applied to a Pressure Swing Adsorption system—0
Surrogate-assisted multi-objective design of complex multibody systems—0
Survey on Hand Gesture Recognition from Visual Input—0
Survival Prediction of Brain Cancer with Incomplete Radiology, Pathology, Genomics, and Demographic Data—0
SUTRA: Scalable Multilingual Language Model Architecture—0
SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training—0
Swarm-STL: A Framework for Motion Planning in Large-Scale, Multi-Swarm Systems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified