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 2561–2570 of 4891 papers

TitleStatusHype
ERes2NetV2: Boosting Short-Duration Speaker Verification Performance with Computational Efficiency—0
Learning Decision Trees and Forests with Algorithmic RecourseCode0
Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach—0
Wasserstein Distributionally Robust Control and State Estimation for Partially Observable Linear Systems—0
Exploiting Frequency Correlation for Hyperspectral Image Reconstruction—0
Multimodal Deep Learning for Low-Resource Settings: A Vector Embedding Alignment Approach for Healthcare Applications—0
A Batch Sequential Halving Algorithm without Performance Degradation—0
Pedestrian intention prediction in Adverse Weather Conditions with Spiking Neural Networks and Dynamic Vision Sensors—0
Modeling Randomly Observed Spatiotemporal Dynamical Systems—0
Effective Interplay between Sparsity and Quantization: From Theory to Practice—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified