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 1181–1190 of 4891 papers

TitleStatusHype
Segregation and Context Aggregation Network for Real-time Cloud Segmentation—0
Optimal Lattice Boltzmann Closures through Multi-Agent Reinforcement Learning—0
Segment Any Crack: Deep Semantic Segmentation Adaptation for Crack Detection—0
Efficient Spiking Point Mamba for Point Cloud Analysis—0
Quantum-Enhanced Reinforcement Learning for Power Grid Security Assessment—0
Integrating Locality-Aware Attention with Transformers for General Geometry PDEs—0
Latent Tensor Factorization with Nonlinear PID Control for Missing Data Recovery in Non-Intrusive Load Monitoring—0
Efficient algorithms for the Hadamard decompositionCode0
Science Hierarchography: Hierarchical Organization of Science LiteratureCode0
MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified