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 4281–4290 of 4891 papers

TitleStatusHype
Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies—0
Efficient Ensembles Improve Training Data Attribution—0
Efficient fine-grained road segmentation using superpixel-based CNN and CRF models—0
Efficient Folded Attention for 3D Medical Image Reconstruction and Segmentation—0
Efficient Frequency Selective Surface Analysis via End-to-End Model-Based Learning—0
Online Importance Sampling for Stochastic Gradient Optimization—0
Efficient Gravitational Wave Parameter Estimation via Knowledge Distillation: A ResNet1D-IAF Approach—0
Efficient identification of linear, parameter-varying, and nonlinear systems with noise models—0
Efficient Image Compression Using Advanced State Space Models—0
Efficient Knowledge Distillation of SAM for Medical Image Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified