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 2291–2300 of 4891 papers

TitleStatusHype
CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty QuantificationCode0
Enhancing Cross-Modality Synthesis: Subvolume Merging for MRI-to-CT Conversion—0
Bridging Autoencoders and Dynamic Mode Decomposition for Reduced-order Modeling and Control of PDEs—0
NeurLZ: An Online Neural Learning-Based Method to Enhance Scientific Lossy Compression—0
Towards Democratizing Multilingual Large Language Models For Medicine Through A Two-Stage Instruction Fine-tuning ApproachCode0
Self-Supervised State Space Model for Real-Time Traffic Accident Prediction Using eKAN NetworksCode0
WaterSeeker: Pioneering Efficient Detection of Watermarked Segments in Large DocumentsCode0
VidLPRO: A Video-Language Pre-training Framework for Robotic and Laparoscopic Surgery—0
An Efficient and Generalizable Symbolic Regression Method for Time Series Analysis—0
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified