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 761–770 of 4891 papers

TitleStatusHype
Emulating Self-attention with Convolution for Efficient Image Super-ResolutionCode2
Language modelling techniques for analysing the impact of human genetic variation—0
Multi-Grained Feature Pruning for Video-Based Human Pose Estimation—0
FastMap: Fast Queries Initialization Based Vectorized HD Map Reconstruction FrameworkCode1
NoT: Federated Unlearning via Weight Negation—0
Machine Learned Force Fields: Fundamentals, its reach, and challenges—0
Geometry-Constrained Monocular Scale Estimation Using Semantic Segmentation for Dynamic Scenes—0
Real-time Spatial-temporal Traversability Assessment via Feature-based Sparse Gaussian ProcessCode2
Neural Configuration-Space Barriers for Manipulation Planning and Control—0
TrafficKAN-GCN: Graph Convolutional-based Kolmogorov-Arnold Network for Traffic Flow OptimizationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified