公开(公告)号：US12045272B2

公开(公告)日：2024-07-23

申请号：US17370899

申请日：2021-07-08

Applicant: ADOBE INC.

Inventor： Saurabh Mahapatra ,  Niyati Chhaya ,  Snehal Raj ,  Sharmila Reddy Nangi ,  Sapthotharan Nair ,  Sagnik Mukherjee ,  Jay Mundra ,  Fan Du ,  Atharv Tyagi ,  Aparna Garimella

IPC: G06F16/34 ,  G06F16/332 ,  G06F40/30 ,  G06N3/04 ,  G06N3/044 ,  G06N3/08

CPC classification number: G06F16/345 ,  G06F16/3329 ,  G06F40/30 ,  G06N3/04 ,  G06N3/044 ,  G06N3/08

Abstract: A text summarization system auto-generates text summarization models using a combination of neural architecture search and knowledge distillation. Given an input dataset for generating/training a text summarization model, neural architecture search is used to sample a search space to select a network architecture for the text summarization model. Knowledge distillation includes fine-tuning a language model for a given text summarization task using the input dataset, and using the fine-tuned language model as a teacher model to inform the selection of the network architecture and the training of the text summarization model. Once a text summarization model has been generated, the text summarization model can be used to generate summaries for given text.

公开(公告)号：US20230020886A1

公开(公告)日：2023-01-19

申请号：US17370899

申请日：2021-07-08

Applicant: ADOBE INC.

Inventor： Saurabh Mahapatra ,  Niyati Chhaya ,  Snehal Raj ,  Sharmila Reddy Nangi ,  Sapthotharan Nair ,  Sagnik Mukherjee ,  Jay Mundra ,  Fan Du ,  Atharv Tyagi ,  Aparna Garimella

IPC: G06F16/34 ,  G06F16/332 ,  G06N3/04 ,  G06N3/08

Abstract: A text summarization system auto-generates text summarization models using a combination of neural architecture search and knowledge distillation. Given an input dataset for generating/training a text summarization model, neural architecture search is used to sample a search space to select a network architecture for the text summarization model. Knowledge distillation includes fine-tuning a language model for a given text summarization task using the input dataset, and using the fine-tuned language model as a teacher model to inform the selection of the network architecture and the training of the text summarization model. Once a text summarization model has been generated, the text summarization model can be used to generate summaries for given text.