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 211–220 of 4891 papers

TitleStatusHype
ConvMAE: Masked Convolution Meets Masked AutoencodersCode2
Toward Fast, Flexible, and Robust Low-Light Image EnhancementCode2
DaViT: Dual Attention Vision TransformersCode2
Efficient Geometry-aware 3D Generative Adversarial NetworksCode2
MOROCCO: Model Resource Comparison FrameworkCode2
PP-OCR: A Practical Ultra Lightweight OCR SystemCode2
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts LayerCode2
U-RWKV: Lightweight medical image segmentation with direction-adaptive RWKVCode1
FADRM: Fast and Accurate Data Residual Matching for Dataset DistillationCode1
Improve Underwater Object Detection through YOLOv12 Architecture and Physics-informed AugmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified