Latest Articles for Data Generation

A method to create tailored datasets for answering questions using diverse information.

New methods aim to improve ECG data privacy and quality.

Discover how diffusion models transform noise into realistic data samples.

A new method improves image generation for autonomous driving in adverse conditions.

New synthetic data methods enhance language-based object detection accuracy and understanding.

KSGAN improves generative models with a unique distance measure for better sample generation.

This article reviews the capabilities and limits of latent diffusion transformers.

A new model uses text to guide LiDAR data creation, reducing costs and improving accuracy.

A look into how diffusion models generate data and their practical uses.

S-SYNTH generates synthetic skin images for better dermatology AI training.

Exploring how diffusion models transform and generate data through systematic noising and de-noising.

A new method reduces computation time in diffusion models while maintaining output quality.

Research shows generative models improve self-supervised learning in time series classification.

Exploring the role of geometric properties in the quality of generated data.

A new method enhances the training of small language models for better conversations.

Exploring how GANs can enhance translation for languages with limited data.

This article discusses a new method for generating synthetic data using various models.

AutoGeo generates high-quality geometric images for AI training.

Study reveals cheaper models may produce better training data for reasoning tasks.

A new model enhances time series generation by capturing simple and complex data features.

Study assesses the creation and evaluation of synthetic satellite images.

COG improves blending of latent variables in generative models.

TCDiff enhances synthetic face creation for better face recognition.

KnoWoGen offers a novel system for creating datasets in knowledge work, addressing key limitations.

A new QGAN architecture improves scalability and data generation quality.

Researchers enhance data generation through the study of Conditional Hierarchical Variational Autoencoders.

A method automates image-text pair generation for remote sensing datasets.

A new method improves traffic scenario generation using natural language inputs.

A new method boosts texture data generation for machine learning models.

A new method transforms tabular data into binary for efficient synthetic data generation.

Research improves data generation in machine learning using synthetic methods for clearer explanations.

A new method for assessing AI agents in customer support via test generation.

A new method to speed up diffusion model output without losing quality.

This paper presents a new approach to creating synthetic data for analysis and modeling.

Free-Mask automates image labeling, enhancing the efficiency of semantic segmentation.

A new approach to generating data using flow matching and Bayesian methods.

Exploring how synthetic data protects privacy while enabling complex data analysis.

Research analyzes the effectiveness of AI-generated images for robot training.

A new method improves training efficiency for diffusion models.

AnySynth offers a new way to create synthetic images for various tasks.