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 2951–2960 of 4891 papers

TitleStatusHype
Feature Aggregating Network with Inter-Frame Interaction for Efficient Video Super-Resolution—0
Subspace Hybrid MVDR Beamforming for Augmented Hearing—0
SAIBench: A Structural Interpretation of AI for Science Through Benchmarks—0
TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly DetectionCode0
LayerCollapse: Adaptive compression of neural networks—0
MobileDiffusion: Instant Text-to-Image Generation on Mobile Devices—0
FakeWatch ElectionShield: A Benchmarking Framework to Detect Fake News for Credible US Elections—0
Spatially Adaptive Cloth Regression with Implicit Neural Representations—0
Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs—0
Online Importance Sampling for Stochastic Gradient Optimization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified