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 651–660 of 4891 papers

TitleStatusHype
PT-PINNs: A Parametric Engineering Turbulence Solver based on Physics-Informed Neural Networks—0
Mixed-gradients Distributed Filtered Reference Least Mean Square Algorithm -- A Robust Distributed Multichannel Active Noise Control Algorithm—0
Token Dynamics: Towards Efficient and Dynamic Video Token Representation for Video Large Language Models—0
Distributed Consensus Optimization with Consensus ALADIN—0
A Pathway to Near Tissue Computing through Processing-in-CTIA Pixels for Biomedical Applications—0
Fast online node labeling with graph subsampling—0
iFlame: Interleaving Full and Linear Attention for Efficient Mesh Generation—0
Comparative Analysis of Deep Learning Models for Real-World ISP Network Traffic ForecastingCode0
Binarized Mamba-Transformer for Lightweight Quad Bayer HybridEVS DemosaicingCode0
Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified