Machine learning-based generation of outputs in augmented reality environments

A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:

• to generate, using a first machine learning model, a first data structure comprising input representations of one or more input components from an augmented reality environment;
• to generate, using a second machine learning model that takes as input at least a portion of the first data structure, a second data structure comprising at least one vector representation characterizing relevance of one or more of the input representations in the first data structure;
• to generate, using a third machine learning model that takes as input at least a portion of the first data structure and at least a portion of the second data structure, an output response;
• and
• to present the output response to a user in the augmented reality environment.

A method comprising:

• generating, using a first machine learning model, a first data structure comprising input representations of one or more input components from an augmented reality environment;
• generating, using a second machine learning model that takes as input at least a portion of the first data structure, a second data structure comprising at least one vector representation characterizing relevance of one or more of the input representations in the first data structure;
• generating, using a third machine learning model that takes as input at least a portion of the first data structure and at least a portion of the second data structure, an output response;
• and
• presenting the output response to a user in the augmented reality environment;
• wherein the method is performed by at least one processing device comprising a processor coupled to a memory.