Abstract: A method, apparatus, non-transitory computer readable medium, and system for data processing include obtaining a question and a plurality of candidate answers to the question, generating an intermediate response based on the question and the plurality of candidate answers, where the intermediate response indicates that a first candidate answer of the plurality of candidate answers is invalid, and generating a response to the question based on the intermediate response, where the response indicates a second candidate answer of the plurality of candidate answers.

Abstract: Techniques discussed herein generally relate to applying machine-learning techniques to design documents to determine relationships among the different style elements within the document. In one example, hypergraph model is trained on a corpus of hypertext markup language (HTML) documents. The trained model is utilized to identifying one or more candidate style elements for a candidate fragment and/or a candidate fragment. Each of the candidates are scored, and at least a portion of the scored candidates are presented as design options for generating a new document.

Abstract: A method, apparatus, and non-transitory computer readable medium for hypergraph processing are described. Embodiments of the present disclosure obtain, by a hypergraph component, a hypergraph that includes a plurality of nodes and a hyperedge, wherein the hyperedge connects the plurality of nodes; perform, by a hypergraph neural network, a node hypergraph convolution based on the hypergraph to obtain an updated node embedding for a node of the plurality of nodes; and generate, by the hypergraph component, an augmented hypergraph based on the updated node embedding.

Abstract: A system and method of digitally monitoring actions of a user on a computing device and providing real-time suggestions to aid the user's task performance. The digital nudging software may perform a range of subtasks successfully. The subtasks may include loading and processing the structured representation of an application to build the graph, identifying the starting point (“Point A”) and the end point (“Point B”) of the path of the user, and conveying a notification of the faster paths in a user-friendly format.