Instabase, Inc.

Vineeth Chinmaya Murthy

Rafal Powalski

Hariharan Thirugnanam

Atinderpal Singh

Sławomir Jan Biel

Kikani Prashant Vinodrai

Bartosz Topolski

Systems and methods for using a machine learning model for a set of one or more documents are disclosed. Exemplary implementations may: create a set of document segments from the set of one or more documents; create a set of semantic vectors; create a query vector that semantically represents a query from a user; determine a subset of the set of semantic vectors based on at least two different comparisons involving the query vector; create a combination of the individual document segments that are associated with the subset of the set of semantic vectors; provide a prompt to the machine learning model, using the created combination of the individual document segments as context; present replies from the machine learning model, and/or perform other steps.

Systems and methods for using a large language model for large documents

Systems and methods for using a text-based document format to provide context for a large language model are disclosed. Exemplary implementations may: obtain an electronic source document in an electronic format; convert the electronic source document to a mark-up document in the text-based document format; obtain a large language model; fine-tune the large language model through a set of documents that are encoded in the text-based document format; provide the mark-up document to the large language model as input for user-directed extraction of information; present a user interface to a user to enable the user to control the user-directed extraction of the information from the mark-up document; and/or other steps.

Systems and methods for using a text-based document format to provide context for a large language model

Systems and methods for using prompt dissection to prompts one or more machine learning models for a set of one or more documents are disclosed. Exemplary implementations may: store a set of document segments from the set of one or more documents; present a user interface to obtain a compound query that includes a first subquery and a second subquery; create subquery vectors that semantically represent the subqueries; determine a subset of a set of semantic vectors based on comparisons with the subquery vectors; create a combination of the individual document segments that are associated with the subset; provide one or more prompts to the one or more machine learning models, using the combination of the individual document segments as context; present replies from the one or more machine learning models, and/or perform other steps.

Growing community of inventors

Bengaluru, India

Vineeth Chinmaya Murthy