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 3191–3200 of 4891 papers

TitleStatusHype
VINNAS: Variational Inference-based Neural Network Architecture Search—0
Vision-Based Road Detection using Contextual Blocks—0
Vision Mamba: Cutting-Edge Classification of Alzheimer's Disease with 3D MRI Scans—0
VISTREAM: Improving Computation Efficiency of Visual Streaming Perception via Law-of-Charge-Conservation Inspired Spiking Neural Network—0
Visualizing Skiers' Trajectories in Monocular Videos—0
Visual Loop Closure Detection Through Deep Graph Consensus—0
Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement—0
Viz: A QLoRA-based Copyright Marketplace for Legally Compliant Generative AI—0
VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving—0
VM-BHINet:Vision Mamba Bimanual Hand Interaction Network for 3D Interacting Hand Mesh Recovery From a Single RGB Image—0
Show:102550
← PrevPage 320 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified