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 3241–3250 of 4891 papers

TitleStatusHype
Zero-shot Image Captioning by Anchor-augmented Vision-Language Space Alignment—0
Zero-Shot Multi-task Hallucination Detection—0
ZigzagPointMamba: Spatial-Semantic Mamba for Point Cloud Understanding—0
1.58-bit FLUX—0
ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs—0
Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry—0
Two-stage Best-scored Random Forest for Large-scale Regression—0
Action recognition with spatial-temporal discriminative filter banks—0
NeuralMatrix: Compute the Entire Neural Networks with Linear Matrix Operations for Efficient Inference—0
Diffusion Models, Image Super-Resolution And Everything: A Survey—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified