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 2021–2030 of 4891 papers

TitleStatusHype
Exact Pareto Optimal Search for Multi-Task Learning and Multi-Criteria Decision-Making—0
FrePolad: Frequency-Rectified Point Latent Diffusion for Point Cloud Generation—0
FreqINR: Frequency Consistency for Implicit Neural Representation with Adaptive DCT Frequency Loss—0
FreqMoE: Dynamic Frequency Enhancement for Neural PDE Solvers—0
FreqPolicy: Frequency Autoregressive Visuomotor Policy with Continuous Tokens—0
Frequency of Interest-based Noise Attenuation Method to Improve Anomaly Detection Performance—0
Class-relevant Patch Embedding Selection for Few-Shot Image Classification—0
An Integer Clustering Approach for Modeling Large-Scale EV Fleets with Guaranteed Performance—0
From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems—0
A Diagrammatic Approach to Improve Computational Efficiency in Group Equivariant Neural Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified