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

Showing 741750 of 4891 papers

TitleStatusHype
MATS: An Interpretable Trajectory Forecasting Representation for Planning and ControlCode1
YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-DesignCode1
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation LearningCode1
Joint Design of RF and gradient waveforms via auto-differentiation for 3D tailored excitation in MRICode1
Revisiting Temporal Modeling for Video Super-resolutionCode1
Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance ProblemsCode1
Corner Proposal Network for Anchor-free, Two-stage Object DetectionCode1
BabyAI 1.1Code1
Backpropagated Gradient Representations for Anomaly DetectionCode1
Graph Neural Networks for Scalable Radio Resource Management: Architecture Design and Theoretical AnalysisCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified