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 1391–1400 of 4891 papers

TitleStatusHype
Decouple to Reconstruct: High Quality UHD Restoration via Active Feature Disentanglement and Reversible Fusion—0
GFSNetwork: Differentiable Feature Selection via Gumbel-Sigmoid RelaxationCode0
Towards Scalable Foundation Model for Multi-modal and Hyperspectral Geospatial Data—0
Personalize Anything for Free with Diffusion Transformer—0
A new graph-based surrogate model for rapid prediction of crashworthiness performance of vehicle panel components—0
AI-Powered Automated Model Construction for Patient-Specific CFD Simulations of Aortic Flows—0
Data-Driven Approximation of Binary-State Network Reliability Function: Algorithm Selection and Reliability Thresholds for Large-Scale Systems—0
Applications of Large Language Model Reasoning in Feature Generation—0
Context-Aware Rule Mining Using a Dynamic Transformer-Based Framework—0
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing flows and the Feynman Kac-FormulaCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified