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 1951–1975 of 4891 papers

TitleStatusHype
Aerodynamic and structural airfoil shape optimisation via Transfer Learning-enhanced Deep Reinforcement Learning—0
3DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification—0
Fire-Image-DenseNet (FIDN) for predicting wildfire burnt area using remote sensing data—0
Alternates, Assemble! Selecting Optimal Alternates for Citizens' Assemblies—0
Approximate Model-Based Diagnosis Using Greedy Stochastic Search—0
DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction—0
Diffusion-Based Joint Temperature and Precipitation Emulation of Earth System Models—0
AL-PINN: Active Learning-Driven Physics-Informed Neural Networks for Efficient Sample Selection in Solving Partial Differential Equations—0
Diffusion-Augmented Coreset Expansion for Scalable Dataset Distillation—0
DiffSHEG: A Diffusion-Based Approach for Real-Time Speech-driven Holistic 3D Expression and Gesture Generation—0
Automated Defect Detection and Grading of Piarom Dates Using Deep Learning—0
FLAME: Flexible LLM-Assisted Moderation Engine—0
Adaptable and Precise: Enterprise-Scenario LLM Function-Calling Capability Training Pipeline—0
Geometric Policy Iteration for Markov Decision Processes—0
FlashMask: Efficient and Rich Mask Extension of FlashAttention—0
DiffRaman: A Conditional Latent Denoising Diffusion Probabilistic Model for Bacterial Raman Spectroscopy Identification Under Limited Data Conditions—0
AutoLoop: Fast Visual SLAM Fine-tuning through Agentic Curriculum Learning—0
GeoLoRA: Geometric integration for parameter efficient fine-tuning—0
Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling—0
Flexible Coded Distributed Convolution Computing for Enhanced Fault Tolerance and Numerical Stability in Distributed CNNs—0
Confidence-Aware Learning Optimal Terminal Guidance via Gaussian Process Regression—0
Flexible Mesh Segmentation via Reeb Graph Representation of Geometrical and Topological Features—0
Configurable Foundation Models: Building LLMs from a Modular Perspective—0
Flexible-weighted Chamfer Distance: Enhanced Objective Function for Point Cloud Completion—0
DiffFNO: Diffusion Fourier Neural Operator—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified