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 761–770 of 4891 papers

TitleStatusHype
Continual Learning For On-Device Environmental Sound ClassificationCode1
PATS: Process-Level Adaptive Thinking Mode SwitchingCode1
Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document EmbeddingsCode1
Camera-Based HRV Prediction for Remote Learning EnvironmentsCode1
PointNorm: Dual Normalization is All You Need for Point Cloud AnalysisCode1
Corner Proposal Network for Anchor-free, Two-stage Object DetectionCode1
CSWin-UNet: Transformer UNet with Cross-Shaped Windows for Medical Image SegmentationCode1
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)Code1
Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNNCode1
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networksCode1
Show:102550
← PrevPage 77 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified