Abstract: Embodiments are disclosed for a method. The method includes receiving an annotation set for a machine learning model. The annotation set includes multiple data points relevant to a task for the machine learning model. The method also includes determining total weights corresponding to the data points. The total weights are determined based on multiple ordering constraints indicating multiple data classes and corresponding weights. The corresponding weights represent a relative priority of the data classes with respect to each other. The method further includes generating an ordered annotation set from the annotation set. The ordered annotation set includes the data points in a sequence based on the determined total weights.

Abstract: Disclosed embodiments provide a framework for implementing automated bots configured to automatically and in real-time process messages exchanged with a user to determine whether to present an opt-in offer for supplemental communications. An agent bot processes ongoing messages exchanged in real-time during a first communications session as these messages are exchanged to determine whether to present an opt-in authorization request for supplemental communications. If the user approves the request, contact information associated with the user is used to facilitate a second communications session through which the user is prompted to provide an opt-in confirmation. The opt-in confirmation and the approval of the opt-in authorization request is provided to allow for transmission of the supplemental communications to the user.