FairCauseSyn couples LLM-based tabular generation with causal fairness constraints, but its own results contradict the key "under 10% deviation" claim and no implementation is released.
Tabfairgan: Fair tabular data generation with generative adversarial networks
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FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation
FairCauseSyn couples LLM-based tabular generation with causal fairness constraints, but its own results contradict the key "under 10% deviation" claim and no implementation is released.