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 1751–1760 of 4891 papers

TitleStatusHype
Bridging Autoencoders and Dynamic Mode Decomposition for Reduced-order Modeling and Control of PDEs—0
CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty QuantificationCode0
Enhancing Cross-Modality Synthesis: Subvolume Merging for MRI-to-CT Conversion—0
Self-Supervised State Space Model for Real-Time Traffic Accident Prediction Using eKAN NetworksCode0
M3-Jepa: Multimodal Alignment via Multi-directional MoE based on the JEPA frameworkCode1
Towards Democratizing Multilingual Large Language Models For Medicine Through A Two-Stage Instruction Fine-tuning ApproachCode0
Consensus-based Distributed Quantum Kernel Learning for Speech Recognition—0
ReL-SAR: Representation Learning for Skeleton Action Recognition with Convolutional Transformers and BYOLCode0
NeurLZ: An Online Neural Learning-Based Method to Enhance Scientific Lossy Compression—0
WaterSeeker: Pioneering Efficient Detection of Watermarked Segments in Large DocumentsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified