Managing inference models using concept-based representations of inferences

Patent metadata

Field	Value
Publication number	US-2025371383-A1
Application number	US-202418678530-A
Country	US
Kind code	A1
Filing date	May 30, 2024
Priority date	May 30, 2024
Publication date	Dec 4, 2025
Grant date	—

Abstract

Methods and systems for managing a generative inference model are disclosed. Using the generative inference model and ingest data, an inference may be obtained. To determine whether the inference is acceptable (e.g., for downstream use, in view of reference works), a set of concepts displayed by the inference may be used to obtain a structured representation of the inference. A comparison process may be performed using the structured representation of the inference and structured representations of the reference works to obtain a level of similarity between the inference and the reference works. Acceptability of the inference may be determined based on the level of similarity and a similarity threshold. If the inference is unacceptable, performance of an action set may be initiated to manage an impact of the level of similarity between the inference and the reference works.

First claim

What is claimed is:

1 . A method for managing a generative inference model, the method comprising:
obtaining an inference generated using the generative inference model and ingest data; analyzing the inference using a schema to obtain a set of concepts displayed by the inference; obtaining a structured representation of the inference based on the set of concepts; performing a comparison process using the structured representation of the inference and structured representations of reference works to obtain a level of similarity between the inference and the reference works; making a determination regarding whether the inference is acceptable based on the level of similarity and a similarity threshold; and in a first instance of the determination where the inference is acceptable:
providing the inference to a downstream consumer as a computer-implemented service; and
in a second instance of the determination where the inference is unacceptable:
initiating performance of an action set to manage an impact of the level of similarity between the inference and the reference works.

2 . The method of claim 1 , wherein the generative inference model is trained to generate human interpretable text when prompted using the ingest data, the human interpretable text being responsive to a request indicated by the ingest data.

3 . The method of claim 1 , wherein the schema is adapted to facilitate identification of at least one of:
a location indicated by the inference; a character indicated by the inference; an object indicated by the inference; and a law of nature indicated by the inference.

4 . The method of claim 1 , wherein the structured representation of the inference comprises a graph-structured data model that specifies relationships between concepts of the set of concepts, the graph-structured data model comprising nodes and edges, and the edges being based on the relationships between the concepts associated with the edges.

5 . The method of claim 1 , wherein performing the comparison process comprises:
performing a sub-graph analysis of the structured representation of the inference with respect to portions of the structured representations of the reference works to identify whether a portion of the structured representation of the inference substantially matches one of the portions of the structured representations of the reference works.

6 . The method of claim 1 , further comprising:
prior to performing the comparison process:
for a portion of the reference works:
analyzing the portion of the reference works to obtain a set of concepts associated with the portion of the reference works; and
obtaining a structured representation of the portion of the reference works based on the set of concepts associated with the portion of the reference works.

7 . The method of claim 1 , wherein the level of similarity indicates a likelihood that the inference plagiarizes the reference works.

8 . The method of claim 1 , wherein the action set comprises obtaining a description of similarities between the inference and the reference works.

9 . The method of claim 1 , wherein the action set comprises preventing provision of the inference to the downstream consumer.

10 . The method of claim 1 , wherein the action set comprises at least one action that, when performed, modifies operation and/or use of the generative inference model to reduce a likelihood that a future inference generated using the generative inference model and the ingest data plagiarizes the reference works.

11 . A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations for managing a generative inference model, the operations comprising:
obtaining an inference generated using the generative inference model and ingest data; analyzing the inference using a schema to obtain a set of concepts displayed by the inference; obtaining a structured representation of the inference based on the set of concepts; performing a comparison process using the structured representation of the inference and structured representations of reference works to obtain a level of similarity between the inference and the reference works; making a determination regarding whether the inference is acceptable based on the level of similarity and a similarity threshold; and in a first instance of the determination where the inference is acceptable: providing the inference to a downstream consumer as a computer-implemented service; and in a second instance of the determination where the inference is unacceptable: initiating performance of an action set to manage an impact of the level of similarity between the inference and the reference works.

12 . The non-transitory machine-readable medium of claim 11 , wherein the generative inference model is trained to generate human interpretable text when prompted using the ingest data, the human interpretable text being responsive to a request indicated by the ingest data.

13 . The non-transitory machine-readable medium of claim 11 , wherein the schema is adapted to facilitate identification of at least one of:
a location indicated by the inference; a character indicated by the inference; an object indicated by the inference; and a law of nature indicated by the inference.

14 . The non-transitory machine-readable medium of claim 11 , wherein the structured representation of the inference comprises a graph-structured data model that specifies relationships between concepts of the set of concepts, the graph-structured data model comprising nodes and edges, and the edges being based on the relationships between the concepts associated with the edges.

15 . The non-transitory machine-readable medium of claim 11 , wherein performing the comparison process comprises:
performing a sub-graph analysis of the structured representation of the inference with respect to portions of the structured representations of the reference works to identify whether a portion of the structured representation of the inference substantially matches one of the portions of the structured representations of the reference works.

16 . A data processing system, comprising:
a processor; and a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations for managing a generative inference model, the operations comprising:
obtaining an inference generated using the generative inference model and ingest data,
analyzing the inference using a schema to obtain a set of concepts displayed by the inference,
obtaining a structured representation of the inference based on the set of concepts,
performing a comparison process using the structured representation of the inference and structured representations of reference works to obtain a level of similarity between the inference and the reference works,
making a determination regarding whether the inference is acceptable based on the level of similarity and a similarity threshold, and
in a first instance of the determination where the inference is acceptable:
providing the inference to a downstream consumer as a computer-implemented service, and

in a second instance of the determination where the inference is unacceptable:
initiating performance of an action set to manage an impact of the level of similarity between the inference and the reference works.

17 . The data processing system of claim 16 , wherein the generative inference model is trained

Assignees

• Dell Products Lp

Inventors

• Ezrielev Ofir
• Kushnir Tomer
• Savir Amihai

Classifications

• G06N5/022

  Knowledge engineering; Knowledge acquisition · CPC title

• G06N20/00

  Machine learning · CPC title

• G06N5/04 Primary

  Inference or reasoning models · CPC title