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 941–950 of 4891 papers

TitleStatusHype
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations—0
Composable Cross-prompt Essay Scoring by Merging Models—0
Advanced Natural-based interaction for the ITAlian language: LLaMAntino-3-ANITA—0
Composite Event Recognition for Maritime Monitoring—0
Composite Gaussian Processes Flows for Learning Discontinuous Multimodal Policies—0
Composite Marginal Likelihood Methods for Random Utility Models—0
Coil Sketching for computationally-efficient MR iterative reconstruction—0
Comprehensive Survey of Model Compression and Speed up for Vision Transformers—0
An Online Prediction Algorithm for Reinforcement Learning with Linear Function Approximation using Cross Entropy Method—0
Cognitive maps are generative programs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified