Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation
Fuente:
arXiv
Guardado en:
| Autores principales: | Long, Yunbo, Xu, Liming, Brintrup, Alexandra |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion
por: Long, Yunbo, et al.
Publicado: (2025)
por: Long, Yunbo, et al.
Publicado: (2025)
Efficient and Privacy-Preserved Link Prediction via Condensed Graphs
por: Long, Yunbo, et al.
Publicado: (2025)
por: Long, Yunbo, et al.
Publicado: (2025)
PA-CFL: Privacy-Adaptive Clustered Federated Learning for Transformer-Based Sales Forecasting on Heterogeneous Retail Data
por: Long, Yunbo, et al.
Publicado: (2025)
por: Long, Yunbo, et al.
Publicado: (2025)
Random Walk Guided Hyperbolic Graph Distillation
por: Long, Yunbo, et al.
Publicado: (2025)
por: Long, Yunbo, et al.
Publicado: (2025)
Generating Logically Consistent Synthetic Supply Chain Data with LLM-Driven Knowledge Graph Reasoning
por: Long, Yunbo, et al.
Publicado: (2026)
por: Long, Yunbo, et al.
Publicado: (2026)
Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training
por: Long, Yunbo, et al.
Publicado: (2026)
por: Long, Yunbo, et al.
Publicado: (2026)
SynDelay: A Synthetic Dataset for Delivery Delay Prediction
por: Xu, Liming, et al.
Publicado: (2025)
por: Xu, Liming, et al.
Publicado: (2025)
Topological Federated Clustering via Gravitational Potential Fields under Local Differential Privacy
por: Long, Yunbo, et al.
Publicado: (2025)
por: Long, Yunbo, et al.
Publicado: (2025)
Structured Evaluation of Synthetic Tabular Data
por: Yang, Scott Cheng-Hsin, et al.
Publicado: (2024)
por: Yang, Scott Cheng-Hsin, et al.
Publicado: (2024)
TuneNSearch: a hybrid transfer learning and local search approach for solving vehicle routing problems
por: Corrêa, Arthur, et al.
Publicado: (2025)
por: Corrêa, Arthur, et al.
Publicado: (2025)
A Comprehensive Survey of Synthetic Tabular Data Generation
por: Shi, Ruxue, et al.
Publicado: (2025)
por: Shi, Ruxue, et al.
Publicado: (2025)
Evaluating Synthetic Tabular Data Generated To Augment Small Sample Datasets
por: Marin, Javier
Publicado: (2022)
por: Marin, Javier
Publicado: (2022)
Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN
por: Sidorenko, Andrey, et al.
Publicado: (2025)
por: Sidorenko, Andrey, et al.
Publicado: (2025)
TAEGAN: Generating Synthetic Tabular Data For Data Augmentation
por: Li, Jiayu, et al.
Publicado: (2024)
por: Li, Jiayu, et al.
Publicado: (2024)
EmoDebt: Bayesian-Optimized Emotional Intelligence for Strategic Agent-to-Agent Debt Recovery
por: Long, Yunbo, et al.
Publicado: (2025)
por: Long, Yunbo, et al.
Publicado: (2025)
Hierarchical Conditional Tabular GAN for Multi-Tabular Synthetic Data Generation
por: Ågren, Wilhelm, et al.
Publicado: (2024)
por: Ågren, Wilhelm, et al.
Publicado: (2024)
Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
por: Villaizán-Vallelado, Mario, et al.
Publicado: (2024)
por: Villaizán-Vallelado, Mario, et al.
Publicado: (2024)
Towards Robust Continual Learning with Bayesian Adaptive Moment Regularization
por: Foster, Jack, et al.
Publicado: (2023)
por: Foster, Jack, et al.
Publicado: (2023)
Robust Spectral Watermark for Synthetic Tabular Data
por: Zhao, Yizhou, et al.
Publicado: (2025)
por: Zhao, Yizhou, et al.
Publicado: (2025)
FEST: A Unified Framework for Evaluating Synthetic Tabular Data
por: Niu, Weijie, et al.
Publicado: (2025)
por: Niu, Weijie, et al.
Publicado: (2025)
Memisis: Orchestrating and Evaluating Synthetic Data for Tabular Health Datasets
por: Nagesh, Nitish, et al.
Publicado: (2026)
por: Nagesh, Nitish, et al.
Publicado: (2026)
CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression
por: Pinheiro, António Pedro, et al.
Publicado: (2025)
por: Pinheiro, António Pedro, et al.
Publicado: (2025)
What's Wrong with Your Synthetic Tabular Data? Using Explainable AI to Evaluate Generative Models
por: Kapar, Jan, et al.
Publicado: (2025)
por: Kapar, Jan, et al.
Publicado: (2025)
Using Reinforcement Learning for the Three-Dimensional Loading Capacitated Vehicle Routing Problem
por: Schoepf, Stefan, et al.
Publicado: (2023)
por: Schoepf, Stefan, et al.
Publicado: (2023)
Synthetic Tabular Data Generation: A Comparative Survey for Modern Techniques
por: Challagundla, Raju, et al.
Publicado: (2025)
por: Challagundla, Raju, et al.
Publicado: (2025)
Structural Consequences of Policy-Based Interventions on the Global Supply Chain Network
por: Karbevska, Lea, et al.
Publicado: (2026)
por: Karbevska, Lea, et al.
Publicado: (2026)
CuTS: Customizable Tabular Synthetic Data Generation
por: Vero, Mark, et al.
Publicado: (2023)
por: Vero, Mark, et al.
Publicado: (2023)
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
por: Stoian, Mihaela Cătălina, et al.
Publicado: (2024)
por: Stoian, Mihaela Cătălina, et al.
Publicado: (2024)
Benchmarking Synthetic Tabular Data: A Multi-Dimensional Evaluation Framework
por: Sidorenko, Andrey, et al.
Publicado: (2025)
por: Sidorenko, Andrey, et al.
Publicado: (2025)
Synthetic Tabular Data Generation for Imbalanced Classification: The Surprising Effectiveness of an Overlap Class
por: D'souza, Annie, et al.
Publicado: (2024)
por: D'souza, Annie, et al.
Publicado: (2024)
TabSynDex: A Universal Metric for Robust Evaluation of Synthetic Tabular Data
por: Chundawat, Vikram S, et al.
Publicado: (2022)
por: Chundawat, Vikram S, et al.
Publicado: (2022)
Potion: Towards Poison Unlearning
por: Schoepf, Stefan, et al.
Publicado: (2024)
por: Schoepf, Stefan, et al.
Publicado: (2024)
Parameter-tuning-free data entry error unlearning with adaptive selective synaptic dampening
por: Schoepf, Stefan, et al.
Publicado: (2024)
por: Schoepf, Stefan, et al.
Publicado: (2024)
Identifying contributors to supply chain outcomes in a multi-echelon setting: a decentralised approach
por: Schoepf, Stefan, et al.
Publicado: (2023)
por: Schoepf, Stefan, et al.
Publicado: (2023)
FASTGEN: Fast and Cost-Effective Synthetic Tabular Data Generation with LLMs
por: Nguyen, Anh, et al.
Publicado: (2025)
por: Nguyen, Anh, et al.
Publicado: (2025)
Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?
por: Swanberg, Marika, et al.
Publicado: (2025)
por: Swanberg, Marika, et al.
Publicado: (2025)
Risk In Context: Benchmarking Privacy Leakage of Foundation Models in Synthetic Tabular Data Generation
por: Byun, Jessup, et al.
Publicado: (2025)
por: Byun, Jessup, et al.
Publicado: (2025)
Towards a Relationship-Aware Transformer for Tabular Data
por: Konstantinov, Andrei V., et al.
Publicado: (2025)
por: Konstantinov, Andrei V., et al.
Publicado: (2025)
SynthEval: A Framework for Detailed Utility and Privacy Evaluation of Tabular Synthetic Data
por: Lautrup, Anton Danholt, et al.
Publicado: (2024)
por: Lautrup, Anton Danholt, et al.
Publicado: (2024)
What if? Causal Machine Learning in Supply Chain Risk Management
por: Wyrembek, Mateusz, et al.
Publicado: (2024)
por: Wyrembek, Mateusz, et al.
Publicado: (2024)
Ejemplares similares
-
LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion
por: Long, Yunbo, et al.
Publicado: (2025) -
Efficient and Privacy-Preserved Link Prediction via Condensed Graphs
por: Long, Yunbo, et al.
Publicado: (2025) -
PA-CFL: Privacy-Adaptive Clustered Federated Learning for Transformer-Based Sales Forecasting on Heterogeneous Retail Data
por: Long, Yunbo, et al.
Publicado: (2025) -
Random Walk Guided Hyperbolic Graph Distillation
por: Long, Yunbo, et al.
Publicado: (2025) -
Generating Logically Consistent Synthetic Supply Chain Data with LLM-Driven Knowledge Graph Reasoning
por: Long, Yunbo, et al.
Publicado: (2026)