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 581–590 of 4891 papers

TitleStatusHype
AsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic SegmentationCode1
Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire DetectionCode1
DeePoly: A High-Order Accuracy Scientific Machine Learning Framework for Function Approximation and Solving PDEsCode1
Deep Speech Synthesis from MRI-Based Articulatory RepresentationsCode1
Efficient Long Sequence Modeling via State Space Augmented TransformerCode1
Efficient Multi-agent Reinforcement Learning by PlanningCode1
AI Accelerator Survey and TrendsCode1
Efficient Neural Network Robustness Certification with General Activation FunctionsCode1
Efficient RAW Image Deblurring with Adaptive Frequency ModulationCode1
Deep Implicit Moving Least-Squares Functions for 3D ReconstructionCode1
Show:102550
← PrevPage 59 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified