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 4201–4210 of 4891 papers

TitleStatusHype
Dual-Priv Pruning : Efficient Differential Private Fine-Tuning in Multimodal Large Language Models—0
Dual-Tree Wavelet Scattering Network with Parametric Log Transformation for Object Classification—0
DUCPS: Deep Unfolding the Cauchy Proximal Splitting Algorithm for B-Lines Quantification in Lung Ultrasound Images—0
Dyna: A Method of Momentum for Stochastic Optimization—0
Dynamic Adaptation in Data Storage: Real-Time Machine Learning for Enhanced Prefetching—0
Dynamic Adaptive Rank Space Exploration for Efficient Sentiment Analysis with Large Language Models—0
Dynamically Expanded CNN Array for Video Coding—0
Dynamic Attention-Guided Context Decoding for Mitigating Context Faithfulness Hallucinations in Large Language Models—0
Dynamic Causal Models of Time-Varying Connectivity—0
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-offs by Selective Execution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified