LANTERN: LLM-Augmented Neurosymbolic Transfer with Experience-Gated Reasoning Networks

ArXi:2605.05478v1 Announce Type: new Transfer learning in reinforcement learning (RL) seeks to accelerate learning in new tasks by leveraging knowledge from related sources. Existing neurosymbolic transfer methods, however, typically rely on manually specified task automata, assume a single source task, and use fixed knowledge-integration mechanisms that cannot adapt to varying source relevance.