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 961–970 of 4891 papers

TitleStatusHype
Certified Error Control of Candidate Set Pruning for Two-Stage Relevance RankingCode0
Heron Inference for Bayesian Graphical ModelsCode0
Hierarchical Variational ModelsCode0
HDKD: Hybrid Data-Efficient Knowledge Distillation Network for Medical Image ClassificationCode0
LightTR: A Lightweight Framework for Federated Trajectory RecoveryCode0
Lightweight Models for Emotional Analysis in VideoCode0
A New Way: Kronecker-Factored Approximate Curvature Deep Hedging and its BenefitsCode0
HDMba: Hyperspectral Remote Sensing Imagery Dehazing with State Space ModelCode0
Linear systems with neural network nonlinearities: Improved stability analysis via acausal Zames-Falb multipliersCode0
HDiffTG: A Lightweight Hybrid Diffusion-Transformer-GCN Architecture for 3D Human Pose EstimationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified