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 2671–2680 of 4891 papers

TitleStatusHype
ST-Mamba: Spatial-Temporal Selective State Space Model for Traffic Flow Prediction—0
AMMUNet: Multi-Scale Attention Map Merging for Remote Sensing Image SegmentationCode0
LEMDA: A Novel Feature Engineering Method for Intrusion Detection in IoT Systems—0
Music Consistency Models—0
A Point-Based Approach to Efficient LiDAR Multi-Task Perception—0
Leveraging Visibility Graphs for Enhanced Arrhythmia Classification with Graph Convolutional NetworksCode0
Proteus: Preserving Model Confidentiality during Graph OptimizationsCode0
Analytical results for uncertainty propagation through trained machine learning regression models—0
Stepwise Alignment for Constrained Language Model Policy OptimizationCode0
LongVQ: Long Sequence Modeling with Vector Quantization on Structured Memory—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified