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 3781–3790 of 4891 papers

TitleStatusHype
BitNet b1.58 2B4T Technical Report—0
Bivariate DeepKriging for Large-scale Spatial Interpolation of Wind Fields—0
Black-box Optimization with Simultaneous Statistical Inference for Optimal Performance—0
Blaze3DM: Marry Triplane Representation with Diffusion for 3D Medical Inverse Problem Solving—0
BlobCtrl: A Unified and Flexible Framework for Element-level Image Generation and Editing—0
Block building programming for symbolic regression—0
Body Transformer: Leveraging Robot Embodiment for Policy Learning—0
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
Boosting Multimodal Reasoning with MCTS-Automated Structured Thinking—0
BOOST: Microgrid Sizing using Ordinal Optimization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified