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 1091–1100 of 4891 papers

TitleStatusHype
Approximation-free Control for Signal Temporal Logic Specifications using Spatiotemporal TubesCode0
RL-DAUNCE: Reinforcement Learning-Driven Data Assimilation with Uncertainty-Aware Constrained Ensembles—0
USPR: Learning a Unified Solver for Profiled RoutingCode0
Mix-QSAM: Mixed-Precision Quantization of the Segment Anything Model—0
UltraGauss: Ultrafast Gaussian Reconstruction of 3D Ultrasound Volumes—0
Lost in OCR Translation? Vision-Based Approaches to Robust Document Retrieval—0
PRE-Mamba: A 4D State Space Model for Ultra-High-Frequent Event Camera Deraining—0
Improved Brain Tumor Detection in MRI: Fuzzy Sigmoid Convolution in Deep Learning—0
RepSNet: A Nucleus Instance Segmentation model based on Boundary Regression and Structural Re-parameterization—0
Learning based convex approximation for constrained parametric optimization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified