Latest Articles for Parameters

A method improves efficiency in training and using large language models.

A new method reduces parameters in transformer models while maintaining performance.

A look at how these models analyze complex data structures across various fields.

Examining the fascinating properties and behaviors of regular black holes.

This article discusses a new approach to measure planet eccentricity using transit data.

A method for fine-tuning language models using fewer parameters.

This research examines the efficiency of backward computation in training language models.

A novel approach to evaluate rare groundwater hazards and enhance management strategies.

Simulated Overparameterization enhances model training while maintaining efficiency.

Learn how long memory influences predictions in various fields.

A look at how effective field theories simplify complex physical systems.

ParFit simplifies parameter fitting in random graph models for effective network analysis.

Detection of eccentric black hole mergers reveals complex cosmic dynamics.

Introducing a dynamic approach to manage Split Completion in graphs effectively.

This study uses machine learning to forecast flame dynamics effectively.

Researchers introduce a method for efficiently analyzing satellite data on atmospheric gases.

A new approach simplifies solving linear equations dependent on numerous parameters.

Innovative methods to analyze cosmic events using advanced neural networks.

A new technique improves parameter management in quantum computing.

A clear breakdown of DDPMs and their practical applications in data generation.

Exploring how certain liquids can exist in multiple forms.

A look at the significance of reaction-diffusion problems in science and engineering.

A look into how we determine parameter values in differential equations.

This article examines nonuniform-dichotomy and its significance in dynamic systems.

A new method to fine-tune large models with improved efficiency.

A look into reducing parameters for better quantum circuit performance.

Research focuses on improving the growth of InAs nanowires using a new model.

A new method improves memory efficiency in training large language models on consumer hardware.

BOSS Net enhances the study of star properties using machine learning.

This model aids in analyzing complex datasets across various fields.

Robots learn to identify arena shapes through local communication and teamwork.

Research aims to improve lung function tests for better diagnosis and treatment.

Examining biases in next-token prediction and their impact on model performance.

Focusing on LayerNorm improves fine-tuning efficiency for BERT models.

A new method improves clarity in analyzing gene interactions using machine learning.

Leveraging NLP to efficiently extract information from lengthy legal judgments.

A new approach to streamline effectful computations in programming languages.

A new approach to reduce CNN complexity while maintaining performance.

Introducing a method for task-agnostic pruning of complex models.

This research presents a combined approach for quicker protein movement simulations.