causal-graphs

EvoCause is a research paper introducing an LLM-guided approach to refine causal graphs for root cause analysis, using expert diagnostic labels to constrain graph edits and releasing TeleRCA, an expert-annotated alarm benchmark from a production telecom network.

This paper introduces HCG-RAG, which uses schema-constrained causal graphs for retrieval-augmented generation, achieving 3-20x fewer nodes and 8x-135x fewer LLM calls while matching or exceeding baseline answer quality on medical benchmarks.

This paper proposes a four-phase method for constructing causal graphs that model LLM inference processes, using counterfactual augmentation to enable stable causal discovery and provide transparent, concept-level explainability.