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 3831–3840 of 4891 papers

TitleStatusHype
Certifiably Robust Interpretation via Renyi Differential Privacy—0
CerviXpert: A Multi-Structural Convolutional Neural Network for Predicting Cervix Type and Cervical Cell Abnormalities—0
CFARNet: Learning-Based High-Resolution Multi-Target Detection for Rainbow Beam Radar—0
CFIS-YOLO: A Lightweight Multi-Scale Fusion Network for Edge-Deployable Wood Defect Detection—0
CFMD: Dynamic Cross-layer Feature Fusion for Salient Object Detection—0
CGP-Tuning: Structure-Aware Soft Prompt Tuning for Code Vulnerability Detection—0
Chain-of-Thought Enhanced Shallow Transformers for Wireless Symbol Detection—0
Change Detection from Synthetic Aperture Radar Images via Dual Path Denoising Network—0
Characteristic Neural Ordinary Differential Equations—0
Characterizing the Evasion Attackability of Multi-label Classifiers—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified