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 931–940 of 4891 papers

TitleStatusHype
A parametric framework for kernel-based dynamic mode decomposition using deep learningCode0
Large Language Model Evaluation via Matrix Nuclear-NormCode0
Hybrid Isolation Forest - Application to Intrusion DetectionCode0
Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference AggregationCode0
Implicit Regularization for Optimal Sparse RecoveryCode0
Inference Scaling vs Reasoning: An Empirical Analysis of Compute-Optimal LLM Problem-SolvingCode0
CIRO: COVID-19 infection risk ontologyCode0
HTR-JAND: Handwritten Text Recognition with Joint Attention Network and Knowledge DistillationCode0
P-Hologen: An End-to-End Generative Framework for Phase-Only HologramsCode0
A denoised Mean Teacher for domain adaptive point cloud registrationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified