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 781–790 of 4891 papers

TitleStatusHype
Union of Experts: Adapting Hierarchical Routing to Equivalently Decomposed TransformerCode0
Enabling Fast, Accurate, and Efficient Real-Time Genome Analysis via New Algorithms and Techniques—0
Multi-Step Deep Koopman Network (MDK-Net) for Vehicle Control in Frenet Frame—0
Correcting Mode Proportion Bias in Generalized Bayesian Inference via a Weighted Kernel Stein Discrepancy—0
Uplink Transmission Design for Fluid Antenna-Enabled Multiuser MIMO Systems with Imperfect CSI—0
ECG-EmotionNet: Nested Mixture of Expert (NMoE) Adaptation of ECG-Foundation Model for Driver Emotion Recognition—0
MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shiftingCode1
Soybean Disease Detection via Interpretable Hybrid CNN-GNN: Integrating MobileNetV2 and GraphSAGE with Cross-Modal Attention—0
Perceptual Motor Learning with Active Inference Framework for Robust Lateral Control—0
From Claims to Evidence: A Unified Framework and Critical Analysis of CNN vs. Transformer vs. Mamba in Medical Image SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified