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 1–10 of 4891 papers

TitleStatusHype
LivePortrait: Efficient Portrait Animation with Stitching and Retargeting ControlCode11
TinyLlama: An Open-Source Small Language ModelCode11
Muon is Scalable for LLM TrainingCode7
PromptWizard: Task-Aware Prompt Optimization FrameworkCode7
Revisiting PCA for time series reduction in temporal dimensionCode7
VMamba: Visual State Space ModelCode7
Enhancing Fourier Neural Operators with Local Spatial FeaturesCode7
RWKV: Reinventing RNNs for the Transformer EraCode6
U-Net v2: Rethinking the Skip Connections of U-Net for Medical Image SegmentationCode6
Mamba: Linear-Time Sequence Modeling with Selective State SpacesCode6
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified