IP Library Granted Patent US 12,461,908
Granted Patent B2
US 12,461,908 · App. 18/651,598 · Granted Nov 4, 2025

System and method for personalizing large language models in query systems

Inventors: Pooja Rajan Chowdhary (Mountain View, CA); Pratik Lala (Mountain View, CA); James Odeyale (Mountain View, CA); Jonathan Lin (Mountain View, CA)
Assignee: INTUIT INC.
G06F16/2425G06F16/24575G06F16/248
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Quick Facts
Patent No.
US 12,461,908
App. No.
18/651,598
Granted
Nov 4, 2025
Kind
B2
Abstract

A system and method are provided for personalizing large language models in query systems.

Claims (42)

1 . A computing system comprising:

a processor; and

a non-transitory computer-readable storage device storing computer-executable instructions, the instructions operable to cause the processor to perform operations comprising:

receiving a user query from a user device;

generating a response to the user query;

feeding the query and the response to a large language model (LLM);

generating a summarized response to the user query via the LLM;

causing the summarized response to be displayed on the user device;

determining a persona of a user associated with the user query, the persona comprising knowledge characteristics of the user;

determining one or more reformatting options based on the persona of the user; and

causing the one or more reformatting options to be displayed on the user device.

2 . The computing system of claim 1 , wherein generating the response to the user query comprises analyzing a knowledge base of information stored in a storage device in communication with the processor.

3 . The computing system of claim 2 , wherein analyzing the knowledge base of information comprises executing a semantic or hybrid vector search within the knowledge base.

4 . The computing system of claim 1 , wherein generating the response to the user query comprises identifying one or more documents relevant to the user query.

5 . The computing system of claim 1 , wherein causing the one or more reformatting options to be displayed on the user device comprises causes an option to present a natural language summary of a code snippet.

6 . The computing system of claim 1 , wherein causing the one or more reformatting options to be displayed on the user device comprises causes an option to convert a code snippet to a different programming language.

7 . The computing system of claim 1 , wherein the operations further comprise:

receiving a user input from the user device selecting one of the one or more reformatting options;

processing the selected reformatting option; and

performing reformatting of the summarized response based on the selected reformatting option.

8 . The computing system of claim 7 , wherein processing the selected reformatting option comprises analyzing a conversation history to identify a message to be reformatted.

9 . The computing system of claim 7 , wherein performing the reformatting of the summarized response based on the selected reformatting option comprises reformatting the summarized response via the LLM.

10 . A computer-implemented method, performed by at least one processor, comprising:

receiving a user query from a user device;

generating a response to the user query;

feeding the query and the response to a large language model (LLM);

generating a summarized response to the user query via the LLM;

causing the summarized response to be displayed on the user device;

determining a persona of a user associated with the user query, the persona comprising knowledge characteristics of the user;

determining one or more reformatting options based on the persona of the user; and

causing the one or more reformatting options to be displayed on the user device.

11 . The computer-implemented method of claim 10 , wherein generating the response to the user query comprises analyzing a knowledge base of information stored in a storage device in communication with the processor.

12 . The computer-implemented method of claim 11 , wherein analyzing the knowledge base of information comprises executing a semantic or hybrid vector search within the knowledge base.

13 . The computer-implemented method of claim 10 , wherein generating the response to the user query comprises identifying one or more documents relevant to the user query.

14 . The computer-implemented method of claim 10 , wherein causing the one or more reformatting options to be displayed on the user device comprises causes an option to present a natural language summary of a code snippet.

15 . The computer-implemented method of claim 10 , wherein causing the one or more reformatting options to be displayed on the user device comprises causes an option to convert a code snippet to a different programming language.

16 . The computer-implemented method of claim 10 comprising:

receiving a user input from the user device selecting one of the one or more reformatting options;

processing the selected reformatting option; and

performing reformatting of the summarized response based on the selected reformatting option.

17 . The computer-implemented method of claim 16 , wherein processing the selected reformatting option comprises analyzing a conversation history to identify a message to be reformatted.

18 . The computer-implemented method of claim 16 , wherein performing the reformatting of the summarized response based on the selected reformatting option comprises reformatting the summarized response via the LLM.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 20, 2024
From: CHOWDHARY, POOJA RAJAN; LALA, PRATIK; ODEYALE, JAMES; LIN, JONATHAN
To: INTUIT INC.
Reel/Frame 069647/0491 →
Continuity (1)
Related Publication 20250335431A1 · Oct 30, 2025
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