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
Latent Neural Operator for Solving Forward and Inverse PDE ProblemsCode2
Parameter-Inverted Image Pyramid NetworksCode2
SoundCTM: Unifying Score-based and Consistency Models for Full-band Text-to-Sound GenerationCode2
Long Context is Not Long at All: A Prospector of Long-Dependency Data for Large Language ModelsCode2
Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent FlowsCode2
AdaFisher: Adaptive Second Order Optimization via Fisher InformationCode2
PoinTramba: A Hybrid Transformer-Mamba Framework for Point Cloud AnalysisCode2
Wav-KAN: Wavelet Kolmogorov-Arnold NetworksCode2
Outlier-robust Kalman Filtering through Generalised BayesCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified