SOTAVerified

Synthetic Data Generation

The generation of tabular data by any means possible.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–400 of 822 papers

TitleStatusHype
GUIDE-VAE: Advancing Data Generation with User Information and Pattern DictionariesCode0
DiffLM: Controllable Synthetic Data Generation via Diffusion Language Models—0
Enhancing Table Representations with LLM-powered Synthetic Data Generation—0
Retrieval-enriched zero-shot image classification in low-resource domains—0
Scalable AI Framework for Defect Detection in Metal Additive Manufacturing—0
Unveiling Synthetic Faces: How Synthetic Datasets Can Expose Real Identities—0
Clinical Evaluation of Medical Image Synthesis: A Case Study in Wireless Capsule Endoscopy—0
Neural spell-checker: Beyond words with synthetic data generationCode0
Synthetic Data Generation with Large Language Models for Personalized Community Question AnsweringCode0
Unpicking Data at the Seams: VAEs, Disentanglement and Independent Components—0
Evaluating utility in synthetic banking microdata applications—0
SoccerGuard: Investigating Injury Risk Factors for Professional Soccer Players with Machine Learning—0
zGAN: An Outlier-focused Generative Adversarial Network For Realistic Synthetic Data Generation—0
Synthetica: Large Scale Synthetic Data for Robot Perception—0
Large Language Model Benchmarks in Medical Tasks—0
Rethinking Data Synthesis: A Teacher Model Training Recipe with Interpretation—0
Little Giants: Synthesizing High-Quality Embedding Data at ScaleCode0
Privacy-hardened and hallucination-resistant synthetic data generation with logic-solvers—0
LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation—0
Sparkle: Mastering Basic Spatial Capabilities in Vision Language Models Elicits Generalization to Composite Spatial Reasoning—0
No more hard prompts: SoftSRV prompting for synthetic data generation—0
Synthetic Data Generation for Residential Load Patterns via Recurrent GAN and Ensemble Method—0
ELOQ: Resources for Enhancing LLM Detection of Out-of-Scope QuestionsCode0
CCUP: A Controllable Synthetic Data Generation Pipeline for Pretraining Cloth-Changing Person Re-Identification ModelsCode0
A Little Human Data Goes A Long WayCode0
Controlled Automatic Task-Specific Synthetic Data Generation for Hallucination Detection—0
CONSULT: Contrastive Self-Supervised Learning for Few-shot Tumor Detection—0
TMGBench: A Systematic Game Benchmark for Evaluating Strategic Reasoning Abilities of LLMsCode0
LLM-based Code-Switched Text Generation for Grammatical Error Correction—0
DFIMat: Decoupled Flexible Interactive Matting in Multi-Person ScenariosCode0
Driving Privacy Forward: Mitigating Information Leakage within Smart Vehicles through Synthetic Data GenerationCode0
JurEE not Judges: safeguarding llm interactions with small, specialised Encoder Ensembles—0
SimpleStrat: Diversifying Language Model Generation with Stratification—0
Unsupervised Data Validation Methods for Efficient Model Training—0
Evaluating Differentially Private Synthetic Data Generation in High-Stakes Domains—0
Fill In The Gaps: Model Calibration and Generalization with Synthetic Data—0
Privacy Vulnerabilities in Marginals-based Synthetic Data—0
Dessie: Disentanglement for Articulated 3D Horse Shape and Pose Estimation from Images—0
Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval Augmented Generation—0
Towards a Theoretical Understanding of Synthetic Data in LLM Post-Training: A Reverse-Bottleneck PerspectiveCode0
Targeted synthetic data generation for tabular data via hardness characterizationCode0
Improved Generation of Synthetic Imaging Data Using Feature-Aligned DiffusionCode0
Restoring Super-High Resolution GPS Mobility Data—0
DreamStruct: Understanding Slides and User Interfaces via Synthetic Data GenerationCode0
DoPAMine: Domain-specific Pre-training Adaptation from seed-guided data Mining—0
Balancing Cost and Effectiveness of Synthetic Data Generation Strategies for LLMs—0
Differentially Private Non Parametric Copulas: Generating synthetic data with non parametric copulas under privacy guarantees—0
Artificial Data Point Generation in Clustered Latent Space for Small Medical Datasets—0
Preserving logical and functional dependencies in synthetic tabular dataCode0
KIPPS: Knowledge infusion in Privacy Preserving 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