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 1001–1010 of 4891 papers

TitleStatusHype
A New Deep-learning-Based Approach For mRNA Optimization: High Fidelity, Computation Efficiency, and Multiple Optimization FactorsCode0
Hard constraint learning approaches with trainable influence functions for evolutionary equationsCode0
HAND: Hierarchical Attention Network for Multi-Scale Handwritten Document Recognition and Layout AnalysisCode0
HADL Framework for Noise Resilient Long-Term Time Series ForecastingCode0
Can RLHF be More Efficient with Imperfect Reward Models? A Policy Coverage PerspectiveCode0
Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random BasesCode0
HDiffTG: A Lightweight Hybrid Diffusion-Transformer-GCN Architecture for 3D Human Pose EstimationCode0
GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated LearningCode0
Guaranteed Multidimensional Time Series Prediction via Deterministic Tensor Completion TheoryCode0
Group and Shuffle: Efficient Structured Orthogonal ParametrizationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified