Invention Grant
- Patent Title: Few-shot language model training and implementation
-
Application No.: US16413159Application Date: 2019-05-15
-
Publication No.: US11062092B2Publication Date: 2021-07-13
- Inventor: Hui Peng Hu
- Applicant: DST Technologies, Inc.
- Applicant Address: US MO Kansas City
- Assignee: DST Technologies, Inc.
- Current Assignee: DST Technologies, Inc.
- Current Assignee Address: US MO Kansas City
- Agency: Perkins Coie LLP
- Agent Colin Fowler; Brian Coleman
- Main IPC: G06F40/30
- IPC: G06F40/30 ; G06N3/08 ; G06F40/263

Abstract:
A technique making use of a few-shot model to determine whether a query text content belongs to a same language as a small set of examples, or alternatively provide a next member in the same language to the small set of examples. The related few-shot model makes use of convolutional models that are trained in a “learning-to-learn” fashion such that the models know how to evaluate few-shots that belong to the same language. The term “language” in this usage is broader than spoken languages (e.g., English, Spanish, German, etc.). “Language” refers to a category, or data domain, of expression through characters. Belonging to a given language is not specifically based on what the language is, but the customs or traits expressed in that language.
Information query