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 2211–2220 of 4891 papers

TitleStatusHype
A Flexible 2.5D Medical Image Segmentation Approach with In-Slice and Cross-Slice AttentionCode1
RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language ProcessingCode3
SuperCLUE-Fin: Graded Fine-Grained Analysis of Chinese LLMs on Diverse Financial Tasks and Applications—0
Landmark Alternating Diffusion—0
Spectral-Spatial Mamba for Hyperspectral Image ClassificationCode1
Open-Source Drift Detection Tools in Action: Insights from Two Use Cases—0
Enhancing Computational Efficiency in Multiscale Systems Using Deep Learning of Coordinates and Flow Maps—0
Implicit Generative Prior for Bayesian Neural NetworksCode0
One-Shot Image Restoration—0
Defect Localization Using Region of Interest and Histogram-Based Enhancement Approaches in 3D-Printing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified