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Synthetic Data Generation

The generation of tabular data by any means possible.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 426–450 of 822 papers

TitleStatusHype
Synthetic Data Generation Techniques for Developing AI-based Speech Assessments for Parkinson's Disease (A Comparative Study)—0
Synthetic Data Generation Using Large Language Models: Advances in Text and Code—0
Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations—0
Synthetic Data Generation with LLM for Improved Depression Prediction—0
Synthetic Data Generators -- Sequential and Private—0
Synthetic Data in AI: Challenges, Applications, and Ethical Implications—0
Synthetic Data Outliers: Navigating Identity Disclosure—0
Synthetic Dataset Generation for Autonomous Mobile Robots Using 3D Gaussian Splatting for Vision Training—0
Synthetic Defect Generation for Display Front-of-Screen Quality Inspection: A Survey—0
Synthetic Embedding-based Data Generation Methods for Student Performance—0
Synthetic Multimodal Question Generation—0
Synthetic News Generation for Fake News Classification—0
Synthetic Point Cloud Generation for Class Segmentation Applications—0
Synthetic Tabular Data: Methods, Attacks and Defenses—0
Synthetic Test Data Generation Using Recurrent Neural Networks: A Position Paper—0
SynthFM: Training Modality-agnostic Foundation Models for Medical Image Segmentation without Real Medical Data—0
SYSTRAN @ WAT 2019: Russian-Japanese News Commentary task—0
TabMT: Generating tabular data with masked transformers—0
TAMIS: Tailored Membership Inference Attacks on Synthetic Data—0
TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation—0
TARGA: Targeted Synthetic Data Generation for Practical Reasoning over Structured Data—0
Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of Large Language Models—0
The Big Data Myth: Using Diffusion Models for Dataset Generation to Train Deep Detection Models—0
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text—0
The Devil in the Details: Simple and Effective Optical Flow Synthetic Data Generation—0
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All datasetsUCI Epileptic Seizure RecognitionUNSW-NB15

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1corGANAUROC0.92—Unverified
2GANAUROC0.87—Unverified
#ModelMetricClaimedVerifiedStatus
1kiNETGANEMD0.07—Unverified
2CTGANEMD0.07—Unverified