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 41–50 of 4891 papers

TitleStatusHype
Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos—0
Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorchCode1
ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset—0
CAM-NET: An AI Model for Whole Atmosphere with Thermosphere and Ionosphere Extension—0
VHU-Net: Variational Hadamard U-Net for Body MRI Bias Field Correction—0
A Multi-Scale Spatial Attention-Based Zero-Shot Learning Framework for Low-Light Image Enhancement—0
Cooperative Bistatic ISAC Systems for Low-Altitude Economy—0
Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT—0
YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual PerceptionCode5
LFR-PINO: A Layered Fourier Reduced Physics-Informed Neural Operator for Parametric PDEs—0
Show:102550
← PrevPage 5 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified