A Tensorflow implementation of QANet for machine reading comprehension on Chinese corpus.
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Updated
Jun 2, 2020 - Python
A Tensorflow implementation of QANet for machine reading comprehension on Chinese corpus.
We implemented QANet from scratch and improved baseline BiDAF. We also used an ensemble of BiDAF and QANet models to achieve EM/F1 of 69.47/71.96, ranking #3 on the leaderboard as of Mar 4, 2022.
Improving Question Answering Performance Using Knowledge Distillation and Active Learning
Tensorflow implementation and pre-trained models of QANet for machine reading comprehension
A TensorFlow implementation of Google's QANet (https://openreview.net/pdf?id=B14TlG-RW)
State of the art of Neural Question Answering using PyTorch.
Tensorflow QANet with ELMo
Includes implementations of various Question-Answering models for the SQuAD dataset and other Research Experiments
a implementation of google QAnet, a tensorflow estimator version, have very good proved performance
Machine Reading Comprehension in Tensorflow
Using QANet and BiDAF on DuReader datasets
Important paper implementations for Question Answering using PyTorch
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