LLM-augmented causal discovery combines edge existence and orientation using Probabilistic Dependency Graphs to fuse Bayesian network structure learning with LLM knowledge
Read the original at arxiv.org→arXiv:2608.27472v1 Announce Type: new Abstract: Bayesian network structure learning (BNSL) from observational data struggles with orientation identifiability, while large language models (LLMs) offer broad but often...
Original headline: "LLM-Augmented Causal Discovery: Probabilistic Fusion of Edge Existence and Orientation"
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- Aug 31, 04:00 UTC arXiv cs.AI lead source LLM-Augmented Causal Discovery: Probabilistic Fusion of Edge Existence and Orientation