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 1311–1320 of 4891 papers

TitleStatusHype
A Time Splitting Based Optimization Method for Nonlinear MHE—0
SpINR: Neural Volumetric Reconstruction for FMCW Radars—0
Unsupervised Learning: Comparative Analysis of Clustering Techniques on High-Dimensional Data—0
Beyond Standard MoE: Mixture of Latent Experts for Resource-Efficient Language Models—0
AuditVotes: A Framework Towards More Deployable Certified Robustness for Graph Neural Networks—0
Action Recognition in Real-World Ambient Assisted Living EnvironmentCode0
A Deep Learning Framework for Boundary-Aware Semantic Segmentation—0
Meta-LoRA: Meta-Learning LoRA Components for Domain-Aware ID Personalization—0
SPDNet: Seasonal-Periodic Decomposition Network for Advanced Residential Demand ForecastingCode0
Next-Best-Trajectory Planning of Robot Manipulators for Effective Observation and Exploration—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified