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 261–270 of 4891 papers

TitleStatusHype
Enhancing Medical Image Registration via Appearance Adjustment NetworksCode1
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent CodingCode1
3D Gaussian Splatting against Moving Objects for High-Fidelity Street Scene ReconstructionCode1
Equivariant Hypergraph Diffusion Neural OperatorsCode1
Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated UncertaintyCode1
Facial Emotion Recognition: State of the Art Performance on FER2013Code1
Fast Sequence Based Embedding with Diffusion GraphsCode1
α-DPO: Adaptive Reward Margin is What Direct Preference Optimization NeedsCode1
BetterNet: An Efficient CNN Architecture with Residual Learning and Attention for Precision Polyp SegmentationCode1
Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context LearningCode1
Show:102550
← PrevPage 27 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified