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 2361–2370 of 4891 papers

TitleStatusHype
Ensemble Prediction via Covariate-dependent StackingCode0
MambaLoc: Efficient Camera Localisation via State Space Model—0
Neural Horizon Model Predictive Control -- Increasing Computational Efficiency with Neural Networks—0
Efficient Budget Allocation for Large-Scale LLM-Enabled Virtual Screening—0
ELASTIC: Efficient Linear Attention for Sequential Interest Compression—0
CTR-KAN: KAN for Adaptive High-Order Feature Interaction ModelingCode0
Bee-yond the Plateau: Training QNNs with Swarm Algorithms—0
ColorMamba: Towards High-quality NIR-to-RGB Spectral Translation with MambaCode0
H_2-optimal Model Reduction of Linear Quadratic Output Systems in Finite Frequency Range—0
Data Clustering and Visualization with Recursive Goemans-Williamson MaxCut Algorithm—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified