Integrating structural causal models into large language models: the PertAdapt framework
To address the systemic flaw of current large-scale language models exhibiting logical deduction failures when faced with out-of-distribution test data and synthetic counterfactual interference, this paper proposes a PertAdapt causal adaptive framework integrating directed acyclic graph constraints. By constructing qua...