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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1991–2000 of 4891 papers

TitleStatusHype
Efficient Spatio-Temporal Signal Recognition on Edge Devices Using PointLCA-Net—0
Beyond Training: Dynamic Token Merging for Zero-Shot Video Understanding—0
Analytical Formula for Fractional-Order Conditional Moments of Nonlinear Drift CEV Process with Regime Switching: Hybrid Approach with Applications—0
Learning Pore-scale Multi-phase Flow from Experimental Data with Graph Neural Network—0
Variational Autoencoders for Efficient Simulation-Based Inference—0
Real-Time Energy-Optimal Path Planning for Electric Vehicles—0
Quantum Attention for Vision Transformers in High Energy Physics—0
LaVida Drive: Vision-Text Interaction VLM for Autonomous Driving with Token Selection, Recovery and Enhancement—0
Moving Horizon Estimation for Simultaneous Localization and Mapping with Robust Estimation Error Bounds—0
Improving Low-Fidelity Models of Li-ion Batteries via Hybrid Sparse Identification of Nonlinear Dynamics—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified