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 2501–2510 of 4891 papers

TitleStatusHype
VeCAF: Vision-language Collaborative Active Finetuning with Training Objective Awareness—0
The Chronicles of RAG: The Retriever, the Chunk and the Generator—0
Input Convex Lipschitz RNN: A Fast and Robust Approach for Engineering TasksCode0
Polariton lattices as binarized neuromorphic networks—0
An ADRC-Incorporated Stochastic Gradient Descent Algorithm for Latent Factor Analysis—0
Image edge enhancement for effective image classification—0
A Physics-informed machine learning model for time-dependent wave runup prediction—0
Plug-in for visualizing 3D tool tracking from videos of Minimally Invasive Surgeries—0
Maximum-Entropy Adversarial Audio Augmentation for Keyword Spotting—0
Data-Efficient Interactive Multi-Objective Optimization Using ParEGO—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified