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 91–100 of 4891 papers

TitleStatusHype
Vectorized Sparse Second-Order Forward Automatic Differentiation for Optimal Control Direct MethodsCode1
A Hybrid Adaptive Nash Equilibrium Solver for Distributed Multi-Agent Systems with Game-Theoretic Jump Triggering—0
Relaxation-Free Min-k-Partition for PCI Assignment in 5G Networks—0
Joint System Modeling Approach for Fault Simulation of Start-er/Generator and Gas Generator in All-Electric APU—0
Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers—0
Structure and asymptotic preserving deep neural surrogates for uncertainty quantification in multiscale kinetic equations—0
High-resolution efficient image generation from WiFi CSI using a pretrained latent diffusion model—0
NeuroPAL: Punctuated Anytime Learning with Neuroevolution for Macromanagement in Starcraft: Brood War—0
It's Not the Target, It's the Background: Rethinking Infrared Small Target Detection via Deep Patch-Free Low-Rank RepresentationsCode1
Slimming Down LLMs Without Losing Their Minds—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified