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 1401–1410 of 4891 papers

TitleStatusHype
Distance-Based Tree-Sliced Wasserstein DistanceCode0
DynRsl-VLM: Enhancing Autonomous Driving Perception with Dynamic Resolution Vision-Language Models—0
SDF-TopoNet: A Two-Stage Framework for Tubular Structure Segmentation via SDF Pre-training and Topology-Aware Fine-TuningCode0
Scalable Global Solution Techniques for High-Dimensional Models in Dynare—0
Pathology Image Compression with Pre-trained Autoencoders—0
Spatio-temporal Fourier Transformer (StFT) for Long-term Dynamics Prediction—0
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing flows and the Feynman Kac-FormulaCode0
CODEI: Resource-Efficient Task-Driven Co-Design of Perception and Decision Making for Mobile Robots Applied to Autonomous Vehicles—0
LVAgent: Long Video Understanding by Multi-Round Dynamical Collaboration of MLLM Agents—0
Evaluating a Novel Neuroevolution and Neural Architecture Search System—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified