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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 621–630 of 4891 papers

TitleStatusHype
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot LearningCode1
Auction-Based Combinatorial Multi-Armed Bandit Mechanisms with Strategic ArmsCode1
GPU optimization of the 3D Scale-invariant Feature Transform Algorithm and a Novel BRIEF-inspired 3D Fast DescriptorCode1
GMSR:Gradient-Guided Mamba for Spectral Reconstruction from RGB ImagesCode1
Gracefully Filtering Backdoor Samples for Generative Large Language Models without RetrainingCode1
A Simple Local Minimal Intensity Prior and An Improved Algorithm for Blind Image DeblurringCode1
DASS: Distilled Audio State Space Models Are Stronger and More Duration-Scalable LearnersCode1
Augmented Lagrangian Adversarial AttacksCode1
BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud RegistrationCode1
Boosting Light-Weight Depth Estimation Via Knowledge DistillationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified