Applying GANs in improving question generation and answering
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Updated
Oct 1, 2017 - Jupyter Notebook
Applying GANs in improving question generation and answering
Neural Models for Key Phrase Detection and Question Generation
A Machine Learning Project Using Python and PHP
This repository uses pretrain BERT embeddings for transfer learning in QA domain
Paraphase Generation
Torch code for Visual Question Generation
An inventory of data sets around Question Generation and Question Answering
Code for paper title "Learning Semantic Sentence Embeddings using Pair-wise Discriminator" COLING-2018
Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation
[ACL 2019]: Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling
☀️A list of question generation papers (with code)
Automatic Question Generation and Short Answer Scoring system
This is a series of R Programs used to randomly generate questions and answers within WMU's D2L E-learning system. Several nice features are included or in production, such as user-friendly function wrappers and clear comments to outline the code. The final results are thousands of multiple-choice questions as D2L-compatible CSV and JPG files.
Neural question generation using transformers
A Tutoring System to help students learn the structured query language, from questions generated from templates. A natural language parser helps to create correct SQL queries from natural language queries for verification.
A summary of must-read papers for Neural Question Generation (NQG)
Comparative techniques for generating quiz questions and scoring answers
Template-Based Question Generation from Retrieved Sentences for Improved Unsupervised Question Answering
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