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 3131–3140 of 4891 papers

TitleStatusHype
EdgeMoE: Fast On-Device Inference of MoE-based Large Language Models—0
NSF: Neural Surface Fields for Human Modeling from Monocular Depth—0
Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Kolmogorov n-width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel—0
QKSAN: A Quantum Kernel Self-Attention Network—0
SGMM: Stochastic Approximation to Generalized Method of Moments—0
Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems—0
VNI-Net: Vector Neurons-based Rotation-Invariant Descriptor for LiDAR Place Recognition—0
Probabilistic load forecasting with Reservoir Computing—0
Reinforcement learning informed evolutionary search for autonomous systems testing—0
Benchmarking Data Efficiency and Computational Efficiency of Temporal Action Localization Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified