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-python

answer-verifier-pytorch

A pytorch implementation of answer verifier for un-answerable question answering.

awesomemrc

This repo is our research summary and playground for MRC. More features are coming.

bank_interview

:bank: 银行笔试面试经验分享及资料分享（help you pass the bank interview, and get a amazing bank offer!）

bert

TensorFlow code and pre-trained models for BERT

bert-race

We are going to explore the multiple choice reading comprehension with bert based on RACE dataset

daanet

DAANet: Dual Ask-Answer Network for Machine Reading Comprehension

data_science

document-qa

flowqa

Implementation of conversational QA model: FlowQA (with slight improvement)

fucking-algorithm

刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

machine_learning_with_python

mrc_book

《机器阅读理解：算法与实践》代码

mtmsn

A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning

multitask-mrc

Multitask Learning for Machine Reading Comprehension, NAACL 2019

nlp-projects

word2vec, sentence2vec, machine reading comprehension, dialog system, text classification, pretrained language model (i.e., XLNet, BERT, ELMo, GPT), sequence labeling, information retrieval, information extraction (i.e., entity, relation and event extraction), knowledge graph, text generation, network embedding

polyu_report_latex_template_library

pytorch-question-answering

Important paper implementations for Question Answering using PyTorch

san_mrc

Stochastic Answer Networks (SAN) for Machine Reading Comprehension

sg-net

SG-Net: Syntax-guided machine reading comprehension (AAAI 2020)

spanbert

Code for using and evaluating SpanBERT.

squad2.0-bert

A Question Answering (QA) model to predict answers for given pairs of context paragraph and question.

stanford-cs224n-qa-project

Ensemble and Multitask Learning with BERT for Question Answering on SQuAD 2.0

strategy

Improving Machine Reading Comprehension with General Reading Strategies

thesis

Minghao Hu's thesis on Machine Reading Comprehension

transformers

🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

unet

The official implementation of paper U-Net: Machine Reading Comprehension with Unanswerable Questions.

xlnet

XLNet: Generalized Autoregressive Pretraining for Language Understanding