Toyota Connected North America, Inc.

Taylor G Smith

Mathew D Gardner

Sebastin Ajay John Jeyaseelan

Tori Salido

Kordel K France

An example operation includes one or more of receiving utterances from a user via an input device, identifying a plurality of sentences spoken by the user from the utterances, converting the utterances into a sequence of tokens and storing the sequence of tokens within a data structure, wherein the storing comprises adding padding tokens to the data structure in between the sequence of tokens to normalize a structure among the plurality of sentences within the data structure, executing a machine learning model on the data structure with the added padding tokens to determine to make a prediction, removing the padding tokens from the data structure, and executing a natural language processing (NLP) model on the sequence of tokens within the data structure with the padding tokens removed to determine a response to the user.

Data structure for task-oriented dialog modeling

System, methods, and other embodiments described herein relate to improving vehicle routing for a mobility service. In one embodiment, a method includes, in response to receiving a routing request for the mobility service, determining candidate vehicles and candidate routes for the candidate vehicles to fulfill the routing request. The method includes evaluating the candidate routes using a meta-heuristic that modifies and assesses the candidate routes according to at least a fitness function defines attributes for constraining the candidate routes. The method includes providing a solution route from the candidate routes upon the solution route satisfying at least one solution condition.

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Allen, TX, United States of America

Taylor G Smith