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 1101–1125 of 4891 papers

TitleStatusHype
A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams—0
Generalized and Efficient 2D Gaussian Splatting for Arbitrary-scale Super-ResolutionCode2
A Short-Term Predict-Then-Cluster Framework for Meal Delivery Services—0
Flash Window Attention: speedup the attention computation for Swin TransformerCode1
A Hybrid Framework for Reinsurance Optimization: Integrating Generative Models and Reinforcement LearningCode0
Universal-2-TF: Robust All-Neural Text Formatting for ASR—0
GenMol: A Drug Discovery Generalist with Discrete Diffusion—0
Efficient Representations for High-Cardinality Categorical Variables in Machine Learning—0
Enhanced Quantile Regression with Spiking Neural Networks for Long-Term System Health Prognostics—0
FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow MatchingCode2
Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration—0
A Unified Framework for Foreground and Anonymization Area Segmentation in CT and MRI DataCode0
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA—0
HyFusion: Enhanced Reception Field Transformer for Hyperspectral Image Fusion—0
On Computational Limits and Provably Efficient Criteria of Visual Autoregressive Models: A Fine-Grained Complexity Analysis—0
CGP-Tuning: Structure-Aware Soft Prompt Tuning for Code Vulnerability Detection—0
SPAR3D: Stable Point-Aware Reconstruction of 3D Objects from Single Images—0
DispFormer: Pretrained Transformer for Flexible Dispersion Curve Inversion from Global Synthesis to Regional ApplicationsCode1
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono—0
Exploring Molecule Generation Using Latent Space Graph DiffusionCode0
Neuromorphic Optical Tracking and Imaging of Randomly Moving Targets through Strongly Scattering Media—0
AuxDepthNet: Real-Time Monocular 3D Object Detection with Depth-Sensitive Features—0
A GPU Implementation of Multi-Guiding Spark Fireworks Algorithm for Efficient Black-Box Neural Network OptimizationCode0
DehazeGS: Seeing Through Fog with 3D Gaussian Splatting—0
The Power of Negative Zero: Datatype Customization for Quantized Large Language ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified