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 1771–1780 of 4891 papers

TitleStatusHype
One-Way Ticket: Time-Independent Unified Encoder for Distilling Text-to-Image Diffusion Models—0
RivuletMLP: An MLP-based Architecture for Efficient Compressed Video Quality Enhancement—0
ACL: Activating Capability of Linear Attention for Image Restoration—0
V2V3D: View-to-View Denoised 3D Reconstruction for Light Field Microscopy—0
Semantic-guided Cross-Modal Prompt Learning for Skeleton-based Zero-shot Action Recognition—0
GPAvatar: High-fidelity Head Avatars by Learning Efficient Gaussian Projections—0
Efficient Test-time Adaptive Object Detection via Sensitivity-Guided Pruning—0
VISTREAM: Improving Computation Efficiency of Visual Streaming Perception via Law-of-Charge-Conservation Inspired Spiking Neural Network—0
Dynamic Group Normalization: Spatio-Temporal Adaptation to Evolving Data Statistics—0
STEPS: Sequential Probability Tensor Estimation for Text-to-Image Hard Prompt Search—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified