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 421–430 of 4891 papers

TitleStatusHype
Unchosen Experts Can Contribute Too: Unleashing MoE Models' Power by Self-ContrastCode1
Efficient Multi-agent Reinforcement Learning by PlanningCode1
Shallow Recurrent Decoder for Reduced Order Modeling of Plasma DynamicsCode1
LighTDiff: Surgical Endoscopic Image Low-Light Enhancement with T-DiffusionCode1
Quantum Vision Transformers for Quark-Gluon ClassificationCode1
GMSR:Gradient-Guided Mamba for Spectral Reconstruction from RGB ImagesCode1
Scalable and Effective Arithmetic Tree Generation for Adder and Multiplier DesignsCode1
RepVGG-GELAN: Enhanced GELAN with VGG-STYLE ConvNets for Brain Tumour DetectionCode1
BetterNet: An Efficient CNN Architecture with Residual Learning and Attention for Precision Polyp SegmentationCode1
A Flexible 2.5D Medical Image Segmentation Approach with In-Slice and Cross-Slice AttentionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified