公开(公告)号：US20230274143A1

公开(公告)日：2023-08-31

申请号：US18173985

申请日：2023-02-24

Applicant: Google LLC

Inventor： Zizhao Zhang ,  Zifeng Wang ,  Chen-Yu Lee ,  Ruoxi Sun ,  Sayna Ebrahimi ,  Xiaoqi Ren ,  Guolong Su ,  Vincent Perot ,  Tomas Pfister ,  Han Zhang

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: A method for rehearsal-free continual learning includes obtaining a set of training samples where training sample in the set of training samples is associated with a respective task of a plurality of different tasks. The method includes obtaining a task-invariant prompt representative of learned knowledge common to each respective task of the plurality of different tasks. The method includes, for each respective task of the plurality of different tasks, obtaining a respective task-specific prompt representative of learned knowledge specific to the respective task. The method includes, during each of one or more training iterations, for each respective training sample in the set of training samples, selecting the respective task-specific prompt representative of the respective task of the respective training sample and training a model using the task-invariant prompt and the selected respective task-specific prompt.

公开(公告)号：US20240153297A1

公开(公告)日：2024-05-09

申请号：US18501982

申请日：2023-11-03

Applicant: Google LLC

Inventor： Zizhao Zhang ,  Zifeng Wang ,  Vincent Perot ,  Jacob Devlin ,  Chen-Yu Lee ,  Guolong Su ,  Hao Zhang ,  Tomas Jon Pfister

IPC: G06V30/24 ,  G06F16/21 ,  G06V30/19 ,  G06V30/412

CPC classification number: G06V30/24 ,  G06F16/211 ,  G06V30/19147 ,  G06V30/412

Abstract: A method for extracting entities comprises obtaining a document that includes a series of textual fields that includes a plurality of entities. Each entity represents information associated with a predefined category. The method includes generating, using the document, a series of tokens representing the series of textual fields. The method includes generating an entity prompt that includes the series of tokens and one of the plurality of entities and generating a schema prompt that includes a schema associated with the document. The method includes generating a model query that includes the entity prompt and the schema prompt and determining, using an entity extraction model and the model query, a location of the one of the plurality of entities among the series of tokens. The method includes extracting, from the document, the one of the plurality of entities using the location of the one of the plurality of entities.