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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3681–3690 of 4891 papers

TitleStatusHype
AI Accelerator Survey and TrendsCode1
LOF: Structure-Aware Line Tracking based on Optical Flow—0
Deep Learning based Model-free Robust Load Restoration to Enhance Bulk System Resilience with Wind Power Penetration—0
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials—0
An MRC Framework for Semantic Role LabelingCode1
Towards a variational Jordan-Lee-Preskill quantum algorithm—0
Adaptive Few-Shot Learning PoC Ultrasound COVID-19 Diagnostic System—0
Robust Predictable Control—0
Near-Field Millimeter-Wave Imaging via Arrays in the Shape of Polyline—0
Voxel Transformer for 3D Object DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified