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 2521–2530 of 4891 papers

TitleStatusHype
Model-Agnostic Interpretation Framework in Machine Learning: A Comparative Study in NBA Sports—0
Migrating Birds Optimization-Based Feature Selection for Text Classification—0
TinyLlama: An Open-Source Small Language ModelCode11
GridFormer: Point-Grid Transformer for Surface ReconstructionCode1
Kernel-U-Net: Multivariate Time Series Forecasting using Custom Kernels—0
SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization—0
HAAQI-Net: A Non-intrusive Neural Music Audio Quality Assessment Model for Hearing AidsCode1
Efficient Parallel Audio Generation using Group Masked Language Modeling—0
Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching—0
Look-Up Table Compression for Efficient Image RestorationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified