Making neural machine reading comprehension faster
Material type:
TextDescription: MSC MI 2017-2019Subject(s): Dissertation note: MSC MI 2017-2019 INT
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | |
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Project Reports
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Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre | Non Fiction | Not for loan | R-1512 |
This study aims at solving the Machine Reading Comprehension problem
where questions have to be answered given a context passage. The challenge is
to develop a computationally faster model which will have improved inference
time. State of the art in many natural language understanding tasks, BERT
model, has been used and knowledge distillation method has been applied to
train two smaller models. The developed models are compared with other
models which have been developed with the same intention.
MSC MI 2017-2019 INT Dr Asharaf S
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