Systems and methods for a k-nearest neighbor based mechanism of natural language processing models
US12265909B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 5, 2020 |
| Grant date | Apr 1, 2025 |
| Priority date | — |
| Expiry date | Jan 21, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments described herein adopts a k nearest neighbor (kNN) mechanism over a model's hidden representations to identify training examples closest to a given test example. Specifically, a training set of sequences and a test sequence are received, each of which is mapped to a respective hidden representation vector using a base model. A set of indices for each sequence index that minimizes a distance between the respective hidden state vector and a test hidden state vector is then determined A weighted k-nearest neighbor probability score can then be computed from the set of indices to generate a probability distribution over labels for the test sequence.
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