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 876–900 of 4891 papers

TitleStatusHype
A Comparison between Markov Chain and Koopman Operator Based Data-Driven Modeling of Dynamical Systems—0
An Unsupervised Approach to Ultrasound Elastography with End-to-end Strain Regularisation—0
Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs—0
3D Shape Reconstruction From Images in the Frequency Domain—0
Critical Nodes Identification in Complex Networks: A Survey—0
An Unconstrained Symmetric Nonnegative Latent Factor Analysis for Large-scale Undirected Weighted Networks—0
A numerically efficient output-only system-identification framework for stochastically forced self-sustained oscillators—0
Advancing clinical trial outcomes using deep learning and predictive modelling: bridging precision medicine and patient-centered care—0
Advancing Brain-Computer Interface System Performance in Hand Trajectory Estimation with NeuroKinect—0
A novel time-frequency Transformer based on self-attention mechanism and its application in fault diagnosis of rolling bearings—0
A Comparative Study on Dynamic Graph Embedding based on Mamba and Transformers—0
A comparative study of human inverse kinematics techniques for lower limbs—0
A novel shape matching descriptor for real-time hand gesture recognition—0
A Novel Noise Injection-based Training Scheme for Better Model Robustness—0
Advances in the Simulation and Modeling of Complex Systems using Dynamical Graph Grammars—0
The Butterfly Effect in Primary Visual Cortex—0
A Novel ML-driven Test Case Selection Approach for Enhancing the Performance of Grammatical Evolution—0
Advances in LLMs with Focus on Reasoning, Adaptability, Efficiency and Ethics—0
Creating generalizable downstream graph models with random projections—0
A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information—0
A Novel Feature Map Enhancement Technique Integrating Residual CNN and Transformer for Alzheimer Diseases Diagnosis—0
A Novel Channel Boosted Residual CNN-Transformer with Regional-Boundary Learning for Breast Cancer Detection—0
A Novel and Optimal Spectral Method for Permutation Synchronization—0
Advances and Open Challenges in Federated Foundation Models—0
A Clustering Method with Graph Maximum Decoding Information—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified