ssanbu08 / deep-paraphrase

Deep models for Paraphrase and Summarization

REFERENCE:

Zhao et al., Adversarially Regularized Autoencoders for Generating Discrete Structures.https://arxiv.org/abs/1706.04223 Git Repo: https://github.com/jakezhaojb/ARAE (Pytorch)

Kim et al., ADVERSARIALLY REGULARIZED AUTOENCODERS https://arxiv.org/pdf/1706.04223.pdf

Gutpa et al, A Deep Generative Framework for Paraphrase Generation. https://arxiv.org/abs/1709.05074. Dataset: https://data.quora.com/First-Quora-Dataset-Release-Question-Pairs

Samuel et al, Generating Sentences from a Continuous Space. https://arxiv.org/abs/1511.06349# Git Repo:https://github.com/kefirski/pytorch_RVAE (Pytorch) Git Repo:https://github.com/Chung-I/Variational-Recurrent-Autoencoder-Tensorflow (TF)

Neural Paraphrase Generation with Stacked Residual LSTM Networks. https://arxiv.org/abs/1610.03098 Git: https://github.com/iamaaditya/neural-paraphrase-generation

Paraphrase Generation with Deep Reinforcement Learning. https://arxiv.org/abs/1711.00279

Learning to Paraphrase for Question Answering. https://arxiv.org/abs/1708.06022

Goodfellow et al, EXPLAINING AND HARNESSING ADVERSARIAL EXAMPLES. https://arxiv.org/abs/1412.6572. (Adversarial training for continous input)

VAE

Hierarchical/ Mixture VAE/

Semi VAE/ Conditional VAE git: https://github.com/wohlert/semi-supervised-pytorch

Deep Recurrent Generative Decoder for Abstractive Text Summarization. https://arxiv.org/abs/1708.00625 Git: https://github.com/toru34/li_emnlp_2017

VAE Tutorial https://arxiv.org/abs/1606.05908

John Paisley http://www.columbia.edu/~jwp2128/Teaching/E6720/BayesianModelsMachineLearning2016.pdf. LECTURE 6 Variational Inference Carl Doersch, Tutorial on Variational Autoencoders, https://arxiv.org/abs/1606.05908

Knowledge Graph

Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks. https://arxiv.org/abs/1704.08384

Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. https://arxiv.org/abs/1607.01426

Compositional Vector Space Models for Knowledge Base Inference. https://www.aaai.org/ocs/index.php/SSS/SSS15/paper/viewFile/10254/10032

Knowledge Graphs: https://people.mpi-inf.mpg.de/~weikum/weikum-adc2015-forwebsite.pdf

Command Lines

data preprocessing python make_datafiles_tokd.py ../data/tokened/ ../data/processed