US 12,406,008 B1
Using intent-based rankings to generate large language model responses
Alberto Cetoli, London (GB); Jason Ryan Engelbrecht, London (GB); Youval Bitner, New York, NY (US); Joel Branch, New York, NY (US); and John E. Ortega, New York, NY (US)
Assigned to CITIBANK, N.A.
Filed by Citibank, N.A., New York, NY (US)
Filed on Jan. 15, 2025, as Appl. No. 19/023,025.
Application 19/023,025 is a continuation of application No. 18/922,212, filed on Oct. 21, 2024, granted, now 12,222,992.
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/906 (2019.01); G06F 16/93 (2019.01)
CPC G06F 16/906 (2019.01) [G06F 16/93 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for causing artificial intelligence (AI) models to generate outputs using intent-based rankings of retrieved information, the computer-implemented method comprising:
obtaining (i) an output generation request for generation of an output using one or more AI models and (ii) one or more sets of information from one or more stored computer files,
wherein the one or more sets of information is responsive to the obtained output generation request;
generating, using a first AI model, a first set of rankings of each set of information of the one or more sets of information by associating each particular set of information with one or more indicators of the obtained output generation request;
classifying, with a set of categorical labels, both (i) the obtained output generation request and (ii) each particular set of information of the one or more sets of information, the set of categorical labels indicating attributes of one or more of: (i) an expected output of the obtained output generation request or (ii) an expected output generation request that results in the particular set of information;
generating, using a second AI model, a second set of rankings of each set of information of the one or more sets of information using (i) the classified set of categorical labels of the obtained output generation request and (ii) the classified set of categorical labels of each set of information of the one or more sets of information; and
using the second set of rankings of the one or more sets of information, causing a generation of one or more outputs responsive to the obtained output generation request.