Gentle Teaching Assistant Model For Improved Accuracy In Question-Answering

Cao, Jinjin; Cao, Jie; Wang, Youquan

doi:10.1145/3578741.3578816

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2023

2024

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Cited by 2 publications

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“…In the article [35], a method known as "an efficient knowledge distillation approach" was applied. To make it more precise, an individual's model is taught more effectively and with fewer constraints by using a more advanced version as "an instructor assistant".…”

Section: Detailed Literaturementioning

confidence: 99%

Deep Learning Based Question Answering System (Survey)

Saeed,

ashraf,

Jhanjhi

2023

Preprint

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Deep learning-based question answering systems have transformed the discipline of natural language processing (NLP) by automating the extraction of answers from textual data. This survey paper provides a captivating overview of these systems, exploring methodologies, techniques, and architectures such as recurrent neural networks (RNNs), BERT model, and transformer models. Extractive and generative approaches are examined, alongside the challenges of handling complex questions, managing noisy input, and addressing rare or unseen words. This survey serves as a stimulating reference, offering valuable insights to researchers and practitioners, fueling innovation and advancement in question answering systems within NLP.

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Section: Detailed Literaturementioning

confidence: 99%