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 1831–1840 of 4891 papers

TitleStatusHype
EE-MLLM: A Data-Efficient and Compute-Efficient Multimodal Large Language Model—0
Approximation of the Proximal Operator of the _ Norm Using a Neural NetworkCode0
UKAN: Unbound Kolmogorov-Arnold Network Accompanied with Accelerated Library—0
A Lightweight Modular Framework for Low-Cost Open-Vocabulary Object Detection TrainingCode0
HMoE: Heterogeneous Mixture of Experts for Language Modeling—0
Ensemble Prediction via Covariate-dependent StackingCode0
Neural Horizon Model Predictive Control -- Increasing Computational Efficiency with Neural Networks—0
ExpoMamba: Exploiting Frequency SSM Blocks for Efficient and Effective Image EnhancementCode1
MambaLoc: Efficient Camera Localisation via State Space Model—0
Implicit Grid Convolution for Multi-Scale Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified