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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 121–130 of 4891 papers

TitleStatusHype
ClearSight: Visual Signal Enhancement for Object Hallucination Mitigation in Multimodal Large language ModelsCode2
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive SurveyCode2
Long Context is Not Long at All: A Prospector of Long-Dependency Data for Large Language ModelsCode2
Grappa -- A Machine Learned Molecular Mechanics Force FieldCode2
SparseLLM: Towards Global Pruning for Pre-trained Language ModelsCode2
A Survey on Diffusion Models for Anomaly DetectionCode2
Harder Tasks Need More Experts: Dynamic Routing in MoE ModelsCode2
GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-MeshCode2
Geometry Aware Operator Transformer as an Efficient and Accurate Neural Surrogate for PDEs on Arbitrary DomainsCode2
GotenNet: Rethinking Efficient 3D Equivariant Graph Neural NetworksCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified