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 2851–2860 of 4891 papers

TitleStatusHype
OMPGPT: A Generative Pre-trained Transformer Model for OpenMP—0
Mitigating the Impact of Noisy Edges on Graph-Based Algorithms via Adversarial Robustness Evaluation—0
Statistical Significance of Feature Importance RankingsCode0
Adaptive Deep Learning for Efficient Visual Pose Estimation aboard Ultra-low-power Nano-drones—0
Linear Periodically Time-Variant Digital PLL Phase Noise Modeling Using Conversion Matrices and Uncorrelated UpsamplingCode0
Spectral Clustering for Discrete Distributions—0
Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence—0
MambaByte: Token-free Selective State Space Model—0
Unified Spatio-Temporal Tri-Perspective View Representation for 3D Semantic Occupancy Prediction—0
RefreshNet: Learning Multiscale Dynamics through Hierarchical Refreshing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified