Abstract: A method (400) performed by a first network node (101). The method includes the first network node obtaining (s402) model performance feedback information (MPFI) for an artificial intelligence (AI) model. The method also includes the first network node providing (s404) the MPFI to a model training function (112). The MPFI provides information that the model training function (112) can use to determine whether the AI model needs to be updated or replaced by a new AI model.

Abstract: Systems and methods are disclosed herein that relate to influencing training of a Machine Learning (ML) model based on a training policy provided by an actor node are disclosed herein. In one embodiment, a method performed by a first node for training a ML model comprises receiving a training policy for a ML model from a second node, the training policy comprising information that indicates two or more accuracy or importance metrics for two or more ranges of values for a variable to be predicted by the ML model. The method further comprises training the ML model based on a training dataset and the training policy. In one embodiment, the first node is either a training and inferring node or a training node that operates to train the ML model, and the second node is an actor node to which predictions made using the ML model are to be provided.

Abstract: Embodiments include methods for a first network node of a wireless network. Such methods include receiving, from a second network node of the wireless network, a first message comprising traffic status information for the second network node and performing one or more of the following operations based on the traffic status information: predicting a change in load and/or interference in a coverage area of the first network node; adjusting configurations of one or more cells and/or one or more beams served by the first network node; requesting the second network node to adjust configurations of one or more cells and/or one or more beams served by the second network node; mobility load balancing with respect to one or more user equipment (UEs) served by the first network node; and configuring one or more UEs served by the first network node to use communication settings that are more robust to interference.