lrh000's repositories
e3
Dockerized code for E3: Entailment-driven Extracting and Editing for Conversational Machine Reading.
Knowledge-Aware-Reader
PyTorch implementation of the ACL 2019 paper "Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader"
converse_reading_cmr
code, data, and model for ACL-19 paper "Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading"
GNNPapers
Must-read papers on graph neural networks (GNN)
practicalAI
📚 A practical approach to learning and using machine learning.
nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
nlp-beginner
NLP上手教程
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
mrc_bert_baseline
A BERT-Based Machine Reading Comprehension Baseline
SMRCToolkit
This toolkit was designed for the fast and efficient development of modern machine comprehension models, including both published models and original prototypes.
CommonSenseMultiHopQA
Code for EMNLP 2018 paper "Commonsense for Generative Multi-Hop Question Answering Tasks"
SDNet
SDNet
san_mrc
Stochastic Answer Networks (SAN) for Machine Reading Comprehension
FlowQA
Implementation of conversational QA model: FlowQA (with slight improvement)
python3-cookbook
《Python Cookbook》 3rd Edition Translation
nmt
TensorFlow Neural Machine Translation Tutorial
bilm-tf
Tensorflow implementation of contextualized word representations from bi-directional language models
adam_qas
ADAM - A Question Answering System. Inspired from IBM Watson
tensor2tensor
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
RCPapers
Must-read papers on Machine Reading Comprehension
graph_nets
Build Graph Nets in Tensorflow
coqa-baselines
The baselines used in the CoQA paper
ChatBotCourse
自己动手做聊天机器人教程
DuReader
Baseline Systems of DuReader Dataset
bi-att-flow
Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.
Group-Normalization-Tensorflow
A TensorFlow implementation of Group Normalization on the task of image classification
learning-nlp
nlp in action
pytorch-book
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation