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 1851–1860 of 4891 papers

TitleStatusHype
PreMixer: MLP-Based Pre-training Enhanced MLP-Mixers for Large-scale Traffic Forecasting—0
Subspace Langevin Monte Carlo—0
E-CAR: Efficient Continuous Autoregressive Image Generation via Multistage Modeling—0
Indirect Query Bayesian Optimization with Integrated Feedback—0
Threshold Neuron: A Brain-inspired Artificial Neuron for Efficient On-device Inference—0
Compressed Sensing Based Residual Recovery Algorithms and Hardware for Modulo Sampling—0
Efficient Oriented Object Detection with Enhanced Small Object Recognition in Aerial Images—0
SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training—0
Design of Restricted Normalizing Flow towards Arbitrary Stochastic Policy with Computational Efficiency—0
Deep Learning for Resilient Adversarial Decision Fusion in Byzantine Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified