Facilitating identification of fillable regions in a form

One or more non-transitory computer-readable storage media storing computer-executable instructions that, when executed by a processing device, cause the processing device to perform operations comprising:

• obtaining a candidate fillable region indicating a position of a region in a form that is a candidate for being fillable, the candidate fillable region generated via a vision machine learning model that analyzes images associated with the form;
• obtaining textual context indicating text from the form and spatial context indicating positions of the text within the form;
• generating a token sequence associated with the candidate fillable region using the textual context and the spatial context, wherein the token sequence comprises a region token representing the candidate fillable region and text tokens representing words from the form that surround the candidate fillable region, the region token and the text tokens being interleaved in the token sequence, to represent a sequence represented in the form, based on position data associated with the text in the form and the candidate fillable region;
• and
• inputting the token sequence into a layout machine learning model to generate fillable region data associated with the candidate fillable region using the token sequence and a type of content format for a fillable region identified via the vision machine learning model in association with the candidate fillable region.

A system comprising one or more hardware processors and a memory component coupled to the one or more hardware processors, the one or more hardware processors to perform operations comprising:

• obtaining a training dataset including a set of forms and training labels indicating positions of fillable regions, textual context indicating words in the set of forms, and spatial context indicating positions of the words in the set of forms;
• and
• training a language machine learning model to generate fillable region data associated with candidate fillable regions, within a form, predicted by a visual machine learning model, wherein the language machine learning model is trained using the training dataset including the set of forms and the training labels indicating the positions of fillable regions, the textual context indicating words in the set of forms, and the spatial context indicating positions of the words in the set of forms, and wherein the trained language machine learning model is used to generate fillable region data that indicates a type of content format for a fillable region, a sub-type of content related to the type of content format for the fillable region, a redundant fillable region, or a combination thereof based on an input token sequence associated with the fillable region, the input token sequence including a region token representing the fillable region interleaved with text tokens representing the words that surround the fillable region, wherein an order of the region token and the text tokens is based on position data of the words and the fillable region.