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 211220 of 4891 papers

TitleStatusHype
An Unforgeable Publicly Verifiable Watermark for Large Language ModelsCode2
SuperFlow++: Enhanced Spatiotemporal Consistency for Cross-Modal Data PretrainingCode2
AlphaNet: Scaling Up Local-frame-based Atomistic Interatomic PotentialCode2
Fast-SNARF: A Fast Deformer for Articulated Neural FieldsCode2
GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-MeshCode2
Learning local equivariant representations for quantum operatorsCode2
Real-Time Polygonal Semantic Mapping for Humanoid Robot Stair ClimbingCode2
Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion DeblurringCode1
Efficient Multi-agent Reinforcement Learning by PlanningCode1
Efficient Neural Implicit Representation for 3D Human ReconstructionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified