/Real-time Identification Of Fact Hallucinations In Artificial Intelligence (ai)
Abstract

An AI query response processed by an artificial intelligence (AI) module using a neural model is received as an input. The query response is compared to one or more tokenized facts of the compressed blocks at a data level. Comparing includes computing a similarity score of a vector derived from the tokenized query response to one or more vectors derived from the one or more tokenized facts. Responsive to a verification result failing to meet a similarity score threshold, it can be determined that a hallucination exists in the AI query response and a policy-based action, such as blocking the AI query response, can be taken. Responsive to the verification result meeting the similarity threshold, the AI query response can be allowed to proceed.

Full Text

What is claimed is:

An AI query response processed by an artificial intelligence (AI) module using a neural model is received as an input. The query response is compared to one or more tokenized facts of the compressed blocks at a data level. Comparing includes computing a similarity score of a vector derived from the tokenized query response to one or more vectors derived from the one or more tokenized facts. Responsive to a verification result failing to meet a similarity score threshold, it can be determined that a hallucination exists in the AI query response and a policy-based action, such as blocking the AI query response, can be taken. Responsive to the verification result meeting the similarity threshold, the AI query response can be allowed to proceed.
Timeline
Filed
04/20/2026
Published
08/27/2026
Granted
Not Available
IPC Codes(1)
G06F 16/2453:Query optimisation