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 2781–2790 of 4891 papers

TitleStatusHype
SNE-RoadSegV2: Advancing Heterogeneous Feature Fusion and Fallibility Awareness for Freespace Detection—0
Real-Time Adaptive Safety-Critical Control with Gaussian Processes in High-Order Uncertain Models—0
Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling—0
STC-ViT: Spatio Temporal Continuous Vision Transformer for Weather Forecasting—0
Comparative Analysis of XGBoost and Minirocket Algortihms for Human Activity Recognition—0
ViTaL: An Advanced Framework for Automated Plant Disease Identification in Leaf Images Using Vision Transformers and Linear Projection For Feature ReductionCode0
Quasi-Bayesian Estimation and Inference with Control Functions—0
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations—0
SDR-Former: A Siamese Dual-Resolution Transformer for Liver Lesion Classification Using 3D Multi-Phase Imaging—0
Dynamic Model of Back-to-Back Converter for System-Level Phasor Simulation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified