TabCausal is a causal discovery foundation model pretrained across diverse synthetic causal environments that reports better macro-averaged performance than baselines on both synthetic and LLM-audited semantic benchmarks.
Stable differentiable causal discovery, 2024
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TabCausal: Pretraining Across Causal Environments for Tabular Causal Discovery
TabCausal is a causal discovery foundation model pretrained across diverse synthetic causal environments that reports better macro-averaged performance than baselines on both synthetic and LLM-audited semantic benchmarks.