A Tensorflow implementation of QANet for machine reading comprehension
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Updated
May 30, 2018 - Python
A Tensorflow implementation of QANet for machine reading comprehension
😎 A curated list of the Question Answering (QA)
Tensorflow Implementation of R-Net
multi_task_NLP is a utility toolkit enabling NLP developers to easily train and infer a single model for multiple tasks.
ALBERT model Pretraining and Fine Tuning using TF2.0
Mining individual characters in multiparty dialogue
Survey on Machine Reading Comprehension
An example for applying FusionNet to Natural Language Inference
A PyTorch implementation of Mnemonic Reader for the Machine Comprehension task
Code for Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine Comprehension
A PyTorch implemention of Match-LSTM, R-NET and M-Reader for Machine Reading Comprehension
A question answering dataset for machine comprehension of spoken content
R-NET implementation in TensorFlow.
ODSQA: OPEN-DOMAIN SPOKEN QUESTION ANSWERING DATASET
Bidirectional Attention Flow for Machine Comprehension implemented in Keras 2
A spoken question answering dataset on SQUAD
Code & data accompanying the IJCAI 2020 paper "GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension"
ReCO: A Large Scale Chinese Reading Comprehension Dataset on Opinion
FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension
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