Cargando…
FewJoint: few-shot learning for joint dialogue understanding
Few-shot learning (FSL) is one of the key future steps in machine learning and raises a lot of attention. In this paper, we focus on the FSL problem of dialogue understanding, which contains two closely related tasks: intent detection and slot filling. Dialogue understanding has been proven to benef...
Autores principales: | Hou, Yutai, Wang, Xinghao, Chen, Cheng, Li, Bohan, Che, Wanxiang, Chen, Zhigang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294856/ https://www.ncbi.nlm.nih.gov/pubmed/35874622 http://dx.doi.org/10.1007/s13042-022-01604-9 |
Ejemplares similares
-
Few-shot learning for joint model in underwater acoustic target recognition
por: Tian, Shengzhao, et al.
Publicado: (2023) -
Meta-Learning for Few-Shot Plant Disease Detection
por: Chen, Liangzhe, et al.
Publicado: (2021) -
Learning few-shot imitation as cultural transmission
por: Bhoopchand, Avishkar, et al.
Publicado: (2023) -
Automatic pavement texture recognition using lightweight few-shot learning
por: Pan, Shuo, et al.
Publicado: (2023) -
High-Dimensional Separability for One- and Few-Shot Learning
por: Gorban, Alexander N., et al.
Publicado: (2021)