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 91–100 of 4891 papers

TitleStatusHype
3D-RCNet: Learning from Transformer to Build a 3D Relational ConvNet for Hyperspectral Image ClassificationCode2
Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence ModelingCode2
LandMarkSystem Technical ReportCode2
LeYOLO, New Scalable and Efficient CNN Architecture for Object DetectionCode2
Hybrid 3D-4D Gaussian Splatting for Fast Dynamic Scene RepresentationCode2
HeadInfer: Memory-Efficient LLM Inference by Head-wise OffloadingCode2
Agent Attention: On the Integration of Softmax and Linear AttentionCode2
Advances in 4D Generation: A SurveyCode2
Grappa -- A Machine Learned Molecular Mechanics Force FieldCode2
2DMamba: Efficient State Space Model for Image Representation with Applications on Giga-Pixel Whole Slide Image ClassificationCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified