Adaptive RAN Slicing Control via Reward-Free Self-Finetuning Agents

ArXi:2603.10564v1 Announce Type: new The integration of Generative AI models into AI-native network systems offers a transformative path toward achieving autonomous and adaptive control. However, the application of such models to continuous control tasks is impeded by intrinsic architectural limitations, including finite context windows, the lack of explicit reward signals, and the degradation of the long context.