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 401–410 of 4891 papers

TitleStatusHype
Nonconvex Linear System Identification with Minimal State Representation—0
Transformer-Empowered Actor-Critic Reinforcement Learning for Sequence-Aware Service Function Chain Partitioning—0
Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation—0
PODNO: Proper Orthogonal Decomposition Neural Operators—0
Outlier-aware Tensor Robust Principal Component Analysis with Self-guided Data Augmentation—0
SSD-Poser: Avatar Pose Estimation with State Space Duality from Sparse Observations—0
TableCenterNet: A one-stage network for table structure recognitionCode1
Towards Robust LLMs: an Adversarial Robustness Measurement FrameworkCode0
A Spatially-Aware Multiple Instance Learning Framework for Digital PathologyCode0
On the workflow, opportunities and challenges of developing foundation model in geophysics—0
Show:102550
← PrevPage 41 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified