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 291–300 of 4891 papers

TitleStatusHype
DiRe-JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale DataCode1
Small but Mighty: Enhancing Time Series Forecasting with Lightweight LLMsCode1
DQO-MAP: Dual Quadrics Multi-Object mapping with Gaussian SplattingCode1
From Claims to Evidence: A Unified Framework and Critical Analysis of CNN vs. Transformer vs. Mamba in Medical Image SegmentationCode1
MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shiftingCode1
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed DistributionsCode1
Long-Context Inference with Retrieval-Augmented Speculative DecodingCode1
PrimeK-Net: Multi-scale Spectral Learning via Group Prime-Kernel Convolutional Neural Networks for Single Channel Speech EnhancementCode1
VesselSAM: Leveraging SAM for Aortic Vessel Segmentation with AtrousLoRACode1
A Reverse Mamba Attention Network for Pathological Liver SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified