Resource-efficient sequence generation with dual-level contrastive learning
US11966428B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 1, 2021 |
| Grant date | Apr 23, 2024 |
| Priority date | — |
| Expiry date | Aug 16, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A training system produces a resource-efficient machine-trained model via a training architecture that employs plural processing paths. Some of the processing paths incorporate the use of auxiliary information that imparts external knowledge about source items being processed. The training architecture also employs contrastive learning that operates at different respective levels within the training architecture. For instance, the training architecture uses encoder-level contrastive learning to compare output information generated by different encoders within the training architecture. The training architecture uses decoder-level contrastive learning to compare output information produced by different decoders within the training architecture. An inference-stage system performs an application task using the model produced by the training system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.