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This paper introduces GoT-CD, a Graph-of-Thoughts method for causal discovery that generates valid DAGs and shows that while structurally competitive with LLM baselines, structural fidelity alone does not guarantee fairness-faithful path-specific audits, highlighting the fragility of post-hoc path-specific fairness auditing.
Graph of Thoughts (GoT) is an open-source Python framework that uses LLMs to solve complex problems by modeling them as graphs of operations, supporting approaches like CoT and ToT.