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

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Showing 1111–1120 of 4891 papers

TitleStatusHype
SAND: One-Shot Feature Selection with Additive Noise Distortion—0
Aerodynamic and structural airfoil shape optimisation via Transfer Learning-enhanced Deep Reinforcement Learning—0
Beyond the model: Key differentiators in large language models and multi-agent services—0
Sparse Ellipsoidal Radial Basis Function Network for Point Cloud Surface RepresentationCode0
Less is More: Efficient Weight Farcasting with 1-Layer Neural Network—0
Continuous Normalizing Flows for Uncertainty-Aware Human Pose Estimation—0
Easz: An Agile Transformer-based Image Compression Framework for Resource-constrained IoTs—0
GauS-SLAM: Dense RGB-D SLAM with Gaussian Surfels—0
Focal-SAM: Focal Sharpness-Aware Minimization for Long-Tailed Classification—0
Stabilizing Temporal Difference Learning via Implicit Stochastic Recursion—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified