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 3161–3170 of 4891 papers

TitleStatusHype
U-Statistics for Importance-Weighted Variational Inference—0
Utility-Based Control for Computer Vision—0
UVCG: Leveraging Temporal Consistency for Universal Video Protection—0
V2V3D: View-to-View Denoised 3D Reconstruction for Light-Field Microscopy—0
V2V3D: View-to-View Denoised 3D Reconstruction for Light Field Microscopy—0
Value-Agnostic Conversational Semantic Parsing—0
Value-of-Information based Arbitration between Model-based and Model-free Control—0
VAMO: Efficient Large-Scale Nonconvex Optimization via Adaptive Zeroth Order Variance Reduction—0
Vanilla Transformers are Transfer Capability Teachers—0
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified