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 2331–2340 of 4891 papers

TitleStatusHype
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer—0
An Efficient Approach to the Online Multi-Agent Path Finding Problem by Using Sustainable Information—0
Efficient Large-Scale Multi-Modal Classification—0
Efficient Language Model Architectures for Differentially Private Federated Learning—0
Efficient Knowledge Distillation of SAM for Medical Image Segmentation—0
An Efficient Approach to Encoding Context for Spoken Language Understanding—0
Adaptive Sampling for Continuous Group Equivariant Neural Networks—0
Accelerating the discovery of low-energy structure configurations: a computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning—0
2.5D Super-Resolution Approaches for X-ray Computed Tomography-based Inspection of Additively Manufactured Parts—0
SPINEX-TimeSeries: Similarity-based Predictions with Explainable Neighbors Exploration for Time Series and Forecasting Problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified