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 751–760 of 4891 papers

TitleStatusHype
Contrast-Phys+: Unsupervised and Weakly-supervised Video-based Remote Physiological Measurement via Spatiotemporal ContrastCode1
Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document EmbeddingsCode1
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic EnvironmentsCode1
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision TransformersCode1
Continual Learning For On-Device Environmental Sound ClassificationCode1
Optimization-Free Test-Time Adaptation for Cross-Person Activity RecognitionCode1
Output Space Entropy Search Framework for Multi-Objective Bayesian OptimizationCode1
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM ImagesCode1
CondenseNet V2: Sparse Feature Reactivation for Deep NetworksCode1
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networksCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified