Systems and methods for shared latent space prompt tuning
US12400073B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 30, 2022 |
| Grant date | Aug 26, 2025 |
| Priority date | — |
| Expiry date | Dec 29, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments described herein provide a prompt-based transfer learning method that employs shared latent space prompt tuning). Specifically, a shared latent space is assumed, among all source and target tasks, where each vector in the space captures a basis skill to do a particular task. Given an instance (from either a source task or a target task), it is first encoded into an instance representation vector and then queries the latent space, which yields a skill vector for this instance. This vector modulates a frozen model, via soft prompts which are a simple prompt transformation (the prompt generator in FIG. 3) of the basis skill vector, to generate an answer for the instance. The latent space and prompt transformation are learned end-to-end in upstream pre-training on source tasks.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.