Systems and methods for text classification using label modular prompts
US12204857B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 28, 2022 |
| Grant date | Jan 21, 2025 |
| Priority date | — |
| Expiry date | Aug 1, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/30
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments described herein provide training a prompt generator for text classification. A first training dataset associated with a first plurality of class labels is received for a first training process. For a first instance of the first training dataset, a set of labels of interest is generated by sampling from a set of possible class labels including the first plurality of class labels. The prompt generator generates a first prompt based on the set of labels of interest. A pretrained language model generates a task output in response to an input of the first instance prepended with the first prompt. A loss objective is generated based on the task output and the set of labels of interest. Parameters of the prompt generator are updated based on the computed loss function via backpropagation while the pretrained language model is frozen.
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