Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimization
Multi-Hop Fact Verification requires complex reasoning across disparate evidence, posing significant challenges for Large Language Models , which may suffer from hallucinations and fractured logical chains. Existing methods, while improving transparency via Chain-of-Thought , often lack explicit modeling of the structural dependencies between evidence and claims. In this work, we introduce an SCM-inspired framework that grounds reasoning in explicit directed dependency graphs, treating verification as a constructive structural reasoning process rather than full causal inference with interventions or counterfactual semantics. We empirically identify an "inverted U-shaped" correlation betwe...
| Authors | Yunhan Bu, Quan Zhang, Huaping Zhang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 2 May 2026 |
| Last updated at source | 23 June 2026 |
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