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 4241–4250 of 4891 papers

TitleStatusHype
Edge Computing for Physics-Driven AI in Computational MRI: A Feasibility Study—0
EDGE++: Improved Training and Sampling of EDGE—0
EdgeMoE: Fast On-Device Inference of MoE-based Large Language Models—0
EE-MLLM: A Data-Efficient and Compute-Efficient Multimodal Large Language Model—0
Effective Interplay between Sparsity and Quantization: From Theory to Practice—0
Effective Real Image Editing with Accelerated Iterative Diffusion Inversion—0
Effects of Reactive Social Distancing on the 1918 Influenza Pandemic—0
EffiCANet: Efficient Time Series Forecasting with Convolutional Attention—0
Efficiency in Real-time Webcam Gaze Tracking—0
Efficient Action Recognition Using Confidence Distillation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified