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 2071–2080 of 4891 papers

TitleStatusHype
Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling—0
CiliaGraph: Enabling Expression-enhanced Hyper-Dimensional Computation in Ultra-Lightweight and One-Shot Graph Classification on Edge—0
Evaluating the effectiveness, reliability and efficiency of a multi-objective sequential optimization approach for building performance design—0
Evaluating Distribution System Reliability with Hyperstructures Graph Convolutional Nets—0
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono—0
An improved chromosome formulation for genetic algorithms applied to variable selection with the inclusion of interaction terms—0
Evaluating Data Influence in Meta Learning—0
Evaluating a Novel Neuroevolution and Neural Architecture Search System—0
Ethics and Technical Aspects of Generative AI Models in Digital Content Creation—0
CHIRRUP: a practical algorithm for unsourced multiple access—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified