Huimu Wang

Structure-grounded reasoning in generative recommendation can dramatically enhance performance, especially when traditional methods struggle with complex item relationships.

LLMs can act as effective action-level supervisors in reinforcement learning, dramatically boosting the sample efficiency of SAC without sacrificing convergence guarantees.