Modeling Extractive Question Answering Using Encoder-Decoder Models with Constrained Decoding and Evaluation-Based Reinforcement Learning

Modeling Extractive Question Answering Using Encoder-Decoder Models with Constrained Decoding and Evaluation-Based Reinforcement Learning

Extractive Question Answering, also known as machine reading comprehension, can be used to evaluate how well a computer comprehends human language. It is a valuable topic with many applications, such as in chatbots and personal assistants. End-to-end neural-network-based models have achieved remarka...

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Detalhes bibliográficos
Principais autores: Shaobo Li, Chengjie Sun, Bingquan Liu, Yuanchao Liu, Zhenzhou Ji
Formato: Artigo
Idioma:English
Publicado em: MDPI AG 2023-03-01
coleção:Mathematics
Assuntos:
natural language processing
question answering
encoder-decoder models
reinforcement learning
neural network
machine learning
Acesso em linha:https://www.mdpi.com/2227-7390/11/7/1624

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https://www.mdpi.com/2227-7390/11/7/1624

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