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
Hyper-CL: Conditioning Sentence Representations with HypernetworksCode1
ARNN: Attentive Recurrent Neural Network for Multi-channel EEG Signals to Identify Epileptic SeizuresCode1
Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural NetworksCode1
Boosting Light-Weight Depth Estimation Via Knowledge DistillationCode1
Calibrating LLMs with Information-Theoretic Evidential Deep LearningCode1
ExpoMamba: Exploiting Frequency SSM Blocks for Efficient and Effective Image EnhancementCode1
Hyperspectral Pansharpening: Critical Review, Tools and Future PerspectivesCode1
Facial Emotion Recognition: State of the Art Performance on FER2013Code1
Improve Underwater Object Detection through YOLOv12 Architecture and Physics-informed AugmentationCode1
Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNNCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified