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 1231–1240 of 4891 papers

TitleStatusHype
V2V3D: View-to-View Denoised 3D Reconstruction for Light-Field Microscopy—0
Probability Estimation and Scheduling Optimization for Battery Swap Stations via LRU-Enhanced Genetic Algorithm and Dual-Factor Decision SystemCode0
How to Detect and Defeat Molecular Mirage: A Metric-Driven Benchmark for Hallucination in LLM-based Molecular Comprehension—0
Deep Reinforcement Learning for Day-to-day Dynamic Tolling in Tradable Credit Schemes—0
STEI-PCN: an efficient pure convolutional network for traffic prediction via spatial-temporal encoding and inferring—0
Search-contempt: a hybrid MCTS algorithm for training AlphaZero-like engines with better computational efficiency—0
A Comparison of Deep Learning Methods for Cell Detection in Digital CytologyCode0
Beyond Reproducibility: Advancing Zero-shot LLM Reranking Efficiency with Setwise Insertion—0
Adapting GT2-FLS for Uncertainty Quantification: A Blueprint Calibration StrategyCode0
Density Approximation of Affine Jump Diffusions via Closed-Form Moment Matching—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified