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

Showing 331340 of 4891 papers

TitleStatusHype
Fast ABC-Boost: A Unified Framework for Selecting the Base Class in Multi-Class ClassificationCode1
Fast and Accurate Entity Recognition with Iterated Dilated ConvolutionsCode1
FastMap: Fast Queries Initialization Based Vectorized HD Map Reconstruction FrameworkCode1
EXTENDING CONDITIONAL CONVOLUTION STRUCTURES FOR ENHANCING MULTITASKING CONTINUAL LEARNINGCode1
Facial Emotion Recognition: State of the Art Performance on FER2013Code1
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PCCode1
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent CodingCode1
ExpoMamba: Exploiting Frequency SSM Blocks for Efficient and Effective Image EnhancementCode1
FADRM: Fast and Accurate Data Residual Matching for Dataset DistillationCode1
Exploring _0 Sparsification for Inference-free Sparse RetrieversCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified