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 1301–1310 of 4891 papers

TitleStatusHype
Diff-GO^n: Enhancing Diffusion Models for Goal-Oriented CommunicationsCode0
Enhancing Scene Coordinate Regression with Efficient Keypoint Detection and Sequential InformationCode1
Adaptive Resolution Residual Networks -- Generalizing Across Resolutions Easily and Efficiently—0
Object Detection using Event Camera: A MoE Heat Conduction based Detector and A New Benchmark DatasetCode2
HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark DetectionCode0
On-Device Self-Supervised Learning of Low-Latency Monocular Depth from Only Events—0
XKV: Personalized KV Cache Memory Reduction for Long-Context LLM Inference—0
FlexDiT: Dynamic Token Density Control for Diffusion TransformerCode1
STONet: A novel neural operator for modeling solute transport in micro-cracked reservoirsCode0
A Tiered GAN Approach for Monet-Style Image Generation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified