Cargando…
On solving textual ambiguities and semantic vagueness in MRC based question answering using generative pre-trained transformers
Machine reading comprehension (MRC) is one of the most challenging tasks and active fields in natural language processing (NLP). MRC systems aim to enable a machine to understand a given context in natural language and to answer a series of questions about it. With the advent of bi-directional deep...
Autores principales: | Ahmed, Muzamil, Khan, Hikmat, Iqbal, Tassawar, Khaled Alarfaj, Fawaz, Alomair, Abdullah, Almusallam, Naif |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403182/ https://www.ncbi.nlm.nih.gov/pubmed/37547420 http://dx.doi.org/10.7717/peerj-cs.1422 |
Ejemplares similares
-
On the Improvement of Default Forecast Through Textual Analysis
por: Cerchiello, Paola, et al.
Publicado: (2020) -
Aspect extraction on user textual reviews using multi-channel convolutional neural network
por: Da’u, Aminu, et al.
Publicado: (2019) -
A knowledge graph based question answering method for medical domain
por: Huang, Xiaofeng, et al.
Publicado: (2021) -
Deep learning-based approach for Arabic open domain question answering
por: Alsubhi, Kholoud, et al.
Publicado: (2022) -
Scaling and Disagreements: Bias, Noise, and Ambiguity
por: Uma, Alexandra, et al.
Publicado: (2022)