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 361–370 of 4891 papers

TitleStatusHype
Efficient Neural Implicit Representation for 3D Human ReconstructionCode1
Scalable Random Feature Latent Variable ModelsCode1
Non-myopic Generation of Language Models for Reasoning and PlanningCode1
Dual Prototype Evolving for Test-Time Generalization of Vision-Language ModelsCode1
Adaptive Data Optimization: Dynamic Sample Selection with Scaling LawsCode1
α-DPO: Adaptive Reward Margin is What Direct Preference Optimization NeedsCode1
Prompt Tuning for Audio Deepfake Detection: Computationally Efficient Test-time Domain Adaptation with Limited Target DatasetCode1
Octopus Inspired Optimization Algorithm: Multi-Level Structures and Parallel Computing StrategiesCode1
Shap-Select: Lightweight Feature Selection Using SHAP Values and RegressionCode1
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time SeriesCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified