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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1701–1725 of 4891 papers

TitleStatusHype
Equivariant Transformers for Neural Network based Molecular Potentials—0
Distributed Consensus Optimization with Consensus ALADIN—0
Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems—0
Ergodic Inference: Accelerate Convergence by Optimisation—0
ERNIE-ViL 2.0: Multi-view Contrastive Learning for Image-Text Pre-training—0
EROAM: Event-based Camera Rotational Odometry and Mapping in Real-time—0
Axial Attention Transformer Networks: A New Frontier in Breast Cancer Detection—0
DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models—0
Distilling Diversity and Control in Diffusion Models—0
Avoiding Obfuscation with Prover-Estimator Debate—0
Fast PET reconstruction using Multi-scale Fully Convolutional Neural Networks—0
Estimation and Applications of Quantile Regression for Binary Longitudinal Data—0
Estimation of Number of Communities in Assortative Sparse Networks—0
Estimation of Parameters for an Archetypal Model of Cardiomyocyte Membrane Potentials—0
FastRef:Fast Prototype Refinement for Few-Shot Industrial Anomaly Detection—0
A VAE-Bayesian Deep Learning Scheme for Solar Generation Forecasting based on Dimensionality Reduction—0
Fast Matching by 2 Lines of Code for Large Scale Face Recognition Systems—0
Evaluating Data Influence in Meta Learning—0
Evaluating Distribution System Reliability with Hyperstructures Graph Convolutional Nets—0
Evaluating the effectiveness, reliability and efficiency of a multi-objective sequential optimization approach for building performance design—0
CiliaGraph: Enabling Expression-enhanced Hyper-Dimensional Computation in Ultra-Lightweight and One-Shot Graph Classification on Edge—0
Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling—0
Evaluating the Evolution of YOLO (You Only Look Once) Models: A Comprehensive Benchmark Study of YOLO11 and Its Predecessors—0
Evaluating the Suitability of Different Intraoral Scan Resolutions for Deep Learning-Based Tooth Segmentation—0
AuxDepthNet: Real-Time Monocular 3D Object Detection with Depth-Sensitive Features—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified