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 831–840 of 4891 papers

TitleStatusHype
Incorporating brain-inspired mechanisms for multimodal learning in artificial intelligenceCode0
Approximate Message Passing with Parameter Estimation for Heavily Quantized MeasurementsCode0
Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory NetworksCode0
Influence Maximization in Temporal Social Networks with a Cold-Start Problem: A Supervised ApproachCode0
Improving Korean NLP Tasks with Linguistically Informed Subword Tokenization and Sub-character DecompositionCode0
Improving Generalization of Medical Image Registration Foundation ModelCode0
Improving Hyper-Relational Knowledge Graph CompletionCode0
Improving Variational Auto-Encoders using Householder FlowCode0
Improving (α, f)-Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distanceCode0
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer VisionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified