Latest Articles for Data Generation

A new method enhances speed and quality in data generation.

Research enhances data generation for validating mathematical proofs using AI.

New methods improve efficiency in face morphing using diffusion models.

A new method improves the quality of generated samples in diffusion models.

Improving sample quality in machine learning through innovative methods.

Flow matching offers a new way to generate data samples efficiently.

A new approach improves RF signal generation for better wireless communication.

Research explores advanced loss functions for improving GAN performance using Genetic Programming.

A breakdown of generative diffusion models and their unique processes.

A method to create data samples based on specific conditions using diffusion models.

Investigating the relationship between symmetry and bit sequences in cryptography.

This article examines how LLMs can generate synthetic tables effectively while addressing key challenges.

RFM improves data generation by managing boundary constraints effectively.

Statistical Flow Matching enhances generative modeling for discrete data challenges.

This paper examines how knowledge transfer enhances generative model accuracy.

Exploring the role of synthetic data in enhancing healthcare AI systems.

APIGen generates diverse, high-quality datasets for function-calling agents.

This article discusses how personas can improve synthetic data creation for training models.

A new method improving sequence generation and decision-making in AI.

Diffusion Models transform data generation and set new standards in quality.

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.