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 2131–2140 of 4891 papers

TitleStatusHype
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis—0
Accurate Hand Keypoint Localization on Mobile Devices—0
Enhancing Multi-hop Reasoning in Vision-Language Models via Self-Distillation with Multi-Prompt Ensembling—0
CD-ROM: Complemented Deep-Reduced Order Model—0
Enhancing Mathematical Reasoning in Large Language Models with Self-Consistency-Based Hallucination Detection—0
Enhancing GNNs Performance on Combinatorial Optimization by Recurrent Feature Update—0
CCSNet: a deep learning modeling suite for CO_2 storage—0
A new robust feature selection method using variance-based sensitivity analysis—0
Enhancing Diffusion Models for High-Quality Image Generation—0
Enhancing Diabetic Retinopathy Diagnosis: A Lightweight CNN Architecture for Efficient Exudate Detection in Retinal Fundus Images—0
Show:102550
← PrevPage 214 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified