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 621–630 of 4891 papers

TitleStatusHype
vGamba: Attentive State Space Bottleneck for efficient Long-range Dependencies in Visual RecognitionCode0
ATP: Adaptive Threshold Pruning for Efficient Data Encoding in Quantum Neural Networks—0
Two for the Price of One: Integrating Large Language Models to Learn Biophysical Interactions—0
Siformer: Feature-isolated Transformer for Efficient Skeleton-based Sign Language RecognitionCode1
ReverBERT: A State Space Model for Efficient Text-Driven Speech Style Transfer—0
Cross-Modal State-Space Graph Reasoning for Structured Summarization—0
Innovative LSGTime Model for Crime Spatiotemporal Prediction Based on MindSpore FrameworkCode0
Optimal Scaling Laws for Efficiency Gains in a Theoretical Transformer-Augmented Sectional MoE Framework—0
Problem-Structure-Informed Quantum Approximate Optimization Algorithm for Large-Scale Unit Commitment with Limited Qubits—0
Novel Deep Neural OFDM Receiver Architectures for LLR EstimationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified