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 2771–2780 of 4891 papers

TitleStatusHype
Source-free Active Domain Adaptation for Diabetic Retinopathy Grading Based on Ultra-wide-field Fundus ImageCode0
Posterior sampling algorithms for unsupervised speech enhancement with recurrent variational autoencoder—0
Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer—0
Asynchronous Perception-Action-Communication with Graph Neural Networks—0
An Autonomous Vision-Based Algorithm for Interplanetary Navigation—0
FrameRS: A Video Frame Compression Model Composed by Self supervised Video Frame Reconstructor and Key Frame SelectorCode0
Decoder-only Architecture for Speech Recognition with CTC Prompts and Text Data Augmentation—0
Astrocyte-Integrated Dynamic Function Exchange in Spiking Neural Networks—0
Efficient Polyp Segmentation Via Integrity Learning—0
Scaling Laws for Sparsely-Connected Foundation Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified