The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 23, 2025

Filed:

Aug. 05, 2020
Applicant:

Siemens Aktiengesellschaft, Munich, DE;

Inventors:

Pankaj Gupta, Munich, DE;

Thomas Runkler, Munich, DE;

Khushbu Saxena, Zürich, CH;

Assignee:

DRIMCO GMBH, Munich, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/00 (2019.01); G06F 16/35 (2019.01); G06F 40/284 (2020.01); G06F 40/40 (2020.01);
U.S. Cl.
CPC ...
G06F 16/35 (2019.01); G06F 40/284 (2020.01); G06F 40/40 (2020.01);
Abstract

Various embodiments of the teachings herein include a computer-implemented method of fine-tuning Natural Language Processing (NLP) models. Some examples include: providing a training data set including a multitude of training text documents; providing a NLP model including a Neural Network (NN) based Topic Model (TM) having scalable TM parameters and a parallel large-scale pre-trained Language Model (LM) having scalable LM parameters; and fine-tuning the NLP model by jointly training the NN-based TM and the parallel large-scale pre-trained LM using a projected vector comprising a combination and projection of a document topic proportion generated by the NN-based TM based on the scalable TM parameters from an input training text document of the multitude of training text documents, and of a contextualized document representation generated by the large-scale pre-trained LM based on the scalable LM parameters from the same input training text document.


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