Multitask learning as question answering
US11615249B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 18, 2020 |
| Grant date | Mar 28, 2023 |
| Priority date | — |
| Expiry date | Apr 11, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/1822
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Approaches for multitask learning as question answering include an input layer for encoding a context and a question, a self-attention based transformer including an encoder and a decoder, a first bi-directional long-term short-term memory (biLSTM) for further encoding an output of the encoder, a long-term short-term memory (LSTM) for generating a context-adjusted hidden state from the output of the decoder and a hidden state, an attention network for generating first attention weights based on an output of the first biLSTM and an output of the LSTM, a vocabulary layer for generating a distribution over a vocabulary, a context layer for generating a distribution over the context, and a switch for generating a weighting between the distributions over the vocabulary and the context, generating a composite distribution based on the weighting, and selecting a word of an answer using the composite distribution.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.