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

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Showing 1341–1350 of 4891 papers

TitleStatusHype
ATP: Adaptive Threshold Pruning for Efficient Data Encoding in Quantum Neural Networks—0
Cross-Modal State-Space Graph Reasoning for Structured Summarization—0
Burst Image Super-Resolution with Mamba—0
SITA: Structurally Imperceptible and Transferable Adversarial Attacks for Stylized Image GenerationCode0
Social Network User Profiling for Anomaly Detection Based on Graph Neural Networks—0
SAFE: Self-Adjustment Federated Learning Framework for Remote Sensing Collaborative Perception—0
Anomaly Detection Using Computer Vision: A Comparative Analysis of Class Distinction and Performance Metrics—0
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems—0
k-NN as a Simple and Effective Estimator of Transferability—0
PALATE: Peculiar Application of the Law of Total Expectation to Enhance the Evaluation of Deep Generative ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified