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 3681–3690 of 4891 papers

TitleStatusHype
A Two-Stage Rotation-Based Super-Resolution Signature Estimation for Spatial Wideband Systems—0
Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement—0
Audio-based Anomaly Detection in Industrial Machines Using Deep One-Class Support Vector Data Description—0
Audio-Plane: Audio Factorization Plane Gaussian Splatting for Real-Time Talking Head Synthesis—0
Audio-Visual Speech Enhancement With Selective Off-Screen Speech Extraction—0
AuditVotes: A Framework Towards More Deployable Certified Robustness for Graph Neural Networks—0
Augmented Space Linear Model—0
A Unified Framework for Sparse Relaxed Regularized Regression: SR3—0
A Unified Framework for Variable Selection in Model-Based Clustering with Missing Not at Random—0
A Unified Module for Accelerating STABLE-DIFFUSION: LCM-LORA—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified