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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2591–2600 of 4891 papers

TitleStatusHype
Feature Aggregating Network with Inter-Frame Interaction for Efficient Video Super-Resolution—0
Mamba: Linear-Time Sequence Modeling with Selective State SpacesCode6
Subspace Hybrid MVDR Beamforming for Augmented Hearing—0
TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly DetectionCode0
LayerCollapse: Adaptive compression of neural networks—0
SAIBench: A Structural Interpretation of AI for Science Through Benchmarks—0
U-Net v2: Rethinking the Skip Connections of U-Net for Medical Image SegmentationCode6
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
Show:102550
← PrevPage 260 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified