US 12,748,784 B2Granted

Iterative response generation using generation schemas

AssigneeVertesia, Inc.

InventorsEric Barroca, Bogdan Stefanescu

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Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for iteratively generating different sections of a textual electronic document (“TED”) using one or more large language models (LLMs). In one aspect, a method comprises receiving a request to generate a TED, generating a generation schema of the TED specifying two or more sections of the TED for separate generation, inputting a first set of commands instructing one or more LLMs to generate a first set of text for a first section of the generation schema, inputting a second set of commands including at least a portion of the first set of text and instructing the LLMs to generate a second set of text for a second section of the generation schema, and creating the TED based on an aggregation of the first set of text and the second text according to the generation schema.

Claims20

Dependent claims

A computer-implemented method comprising:

receiving, by a system that is connected between a client device and one or more large language models (LLMs), a request to generate a textual electronic document (“TED”) from a client device;
generating, based on the request, a generation schema of the TED, wherein the generation schema specifies two or more sections of the TED that will be separately generated;
inputting, by the system and to the one or more LLMs, a first set of data including (i) the generation schema, (ii) data from the request, and (iii) a first set of commands instructing the one or more LLMs to generate a first set of text for a first section of the generation schema of the TED based on the first set of data;
obtaining, by the system and from the one or more LLMs, a first response to the first set of data, wherein the first response includes the first set of text generated for the first section of the generation schema of the TED;
creating, by the system, a second set of data including (i) the generation schema, (ii) the data from the request, (iii) at least a portion of the first set of text generated for the first section of the generation schema, and (iv) a second set of commands instructing the one or more LLMs to generate a second set of text for a second section of the generation schema of the TED based on the second set of data;
submitting, by the system, the second set of data to the one or more LLMs;
obtaining, by the system, a second response to the second set of data, wherein the second response includes the second set of text generated for the second section of the generation schema of the TED;
creating, by the system, the TED based on an aggregation of the first set of text and the second text according to the generation schema;
and
providing, by the system, a graphical representation of the TED to the client device in response to the request.

7 more elements

A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:

receiving, by a system that is connected between a client device and one or more large language models (LLMs), a request to generate a textual electronic document (“TED”) from a client device;
generating, based on the request, a generation schema of the TED, wherein the generation schema specifies two or more sections of the TED that will be separately generated;
inputting, by the system and to the one or more LLMs, a first set of data including (i) the generation schema, (ii) data from the request, and (iii) a first set of commands instructing the one or more LLMs to generate a first set of text for a first section of the generation schema of the TED based on the first set of data;
obtaining, by the system and from the one or more LLMs, a first response to the first set of data, wherein the first response includes the first set of text generated for the first section of the generation schema of the TED;
creating, by the system, a second set of data including (i) the generation schema, (ii) the data from the request, (iii) at least a portion of the first set of text generated for the first section of the generation schema, and (iv) a second set of commands instructing the one or more LLMs to generate a second set of text for a second section of the generation schema of the TED based on the second set of data;
submitting, by the system, the second set of data to the one or more LLMs;
obtaining, by the system, a second response to the second set of data, wherein the second response includes the second set of text generated for the second section of the generation schema of the TED;
creating, by the system, the TED based on an aggregation of the first set of text and the second text according to the generation schema;
and
providing, by the system, a graphical representation of the TED to the client device in response to the request.

7 more elements

A non-transitory computer readable storage medium encoded with a computer program, the program comprising instructions that are operable, when executed by data processing apparatus, to cause the data processing apparatus to perform operations comprising:

receiving, by a system that is connected between a client device and one or more large language models (LLMs), a request to generate a textual electronic document (“TED”) from a client device;
generating, based on the request, a generation schema of the TED, wherein the generation schema specifies two or more sections of the TED that will be separately generated;
inputting, by the system and to the one or more LLMs, a first set of data including (i) the generation schema, (ii) data from the request, and (iii) a first set of commands instructing the one or more LLMs to generate a first set of text for a first section of the generation schema of the TED based on the first set of data;
obtaining, by the system and from the one or more LLMs, a first response to the first set of data, wherein the first response includes the first set of text generated for the first section of the generation schema of the TED;
creating, by the system, a second set of data including (i) the generation schema, (ii) the data from the request, (iii) at least a portion of the first set of text generated for the first section of the generation schema, and (iv) a second set of commands instructing the one or more LLMs to generate a second set of text for a second section of the generation schema of the TED based on the second set of data;
submitting, by the system, the second set of data to the one or more LLMs;
obtaining, by the system, a second response to the second set of data, wherein the second response includes the second set of text generated for the second section of the generation schema of the TED;
creating, by the system, the TED based on an aggregation of the first set of text and the second text according to the generation schema;
and
providing, by the system, a graphical representation of the TED to the client device in response to the request.

7 more elements

Dependencies are inferred from the claim text.

Facts

Application: 19/013,323Filed 8 Jan 2025
Published: US 2026/0195352 A19 Jul 2026
Granted: 29 Sep 2026
Term ends: Not estimatedThe source records don’t support an estimate.

Classification12 codes

G06F 16/3328
Using relevance feedback from the user, e.g. relevance feedback on documents, documents sets, document terms or passages: using graphical result…
G06F 40/56
Rule-based translation: natural language generation
G06F 40/131
Use of codes for handling textual entities: fragmentation of text files, e.g. creating reusable text-blocks; Linking to fragments, e.g. using…
G06F 40/166
Text processing: editing, e.g. inserting or deleting