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 1951–1960 of 4891 papers

TitleStatusHype
An Integrated Artificial Intelligence Operating System for Advanced Low-Altitude Aviation Applications—0
Deep Plug-and-Play HIO Approach for Phase Retrieval—0
Controlling Participation in Federated Learning with FeedbackCode0
Robust Offline Reinforcement Learning with Linearly Structured f-Divergence Regularization—0
Randomized-Grid Search for Hyperparameter Tuning in Decision Tree Model to Improve Performance of Cardiovascular Disease Classification—0
RS-vHeat: Heat Conduction Guided Efficient Remote Sensing Foundation Model—0
Dynamic Logistic Ensembles with Recursive Probability and Automatic Subset Splitting for Enhanced Binary ClassificationCode0
On the Effectiveness of Incremental Training of Large Language ModelsCode0
Residual Attention Single-Head Vision Transformer Network for Rolling Bearing Fault Diagnosis in Noisy Environments—0
A Runtime-Adaptive Transformer Neural Network Accelerator on FPGAsCode0
Show:102550
← PrevPage 196 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified