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 1981–1990 of 4891 papers

TitleStatusHype
OSPC: Artificial VLM Features for Hateful Meme Detection—0
Feature-Specific Coefficients of Determination in Tree Ensembles—0
Improving Conversational Abilities of Quantized Large Language Models via Direct Preference Alignment—0
LivePortrait: Efficient Portrait Animation with Stitching and Retargeting ControlCode11
Plant Doctor: A hybrid machine learning and image segmentation software to quantify plant damage in video footage—0
Classification of Power Quality Disturbances Using Resnet with Channel Attention Mechanism—0
UltraPixel: Advancing Ultra-High-Resolution Image Synthesis to New Peaks—0
OpenSlot: Mixed Open-Set Recognition with Object-Centric Learning—0
DiGRAF: Diffeomorphic Graph-Adaptive Activation FunctionCode1
On the Robustness of Graph Reduction Against GNN Backdoor—0
Show:102550
← PrevPage 199 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified