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 2631–2640 of 4891 papers

TitleStatusHype
Class-relevant Patch Embedding Selection for Few-Shot Image Classification—0
LightTR: A Lightweight Framework for Federated Trajectory RecoveryCode0
Boosting MLPs with a Coarsening Strategy for Long-Term Time Series ForecastingCode0
Fast TILs -- A Pipeline for Efficient TILs Estimation in Non-Small Cell Lung Cancer—0
Off-OAB: Off-Policy Policy Gradient Method with Optimal Action-Dependent Baseline—0
TLINet: Differentiable Neural Network Temporal Logic Inference—0
Dependency-Aware Semi-Structured Sparsity of GLU Variants in Large Language Models—0
Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric spaceCode0
Holistic Evaluation Metrics: Use Case Sensitive Evaluation Metrics for Federated Learning—0
RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified