Embedding

  • learning representations by back-propagating errors, PDF (Hinton 1986, distributed representation)
  • A Neural Probabilistic Language Model, PDF Bengio 2003
  • Efficient Estimation of Word Representations in Vector Space, PDF T Mikolov 2013
  • Sequence to Sequence Learning with Neural Networks, PDF NIPS 2014 Google
  • Semi-supervised Sequence Learning, PDF NIPS 2015 Google

  • Distributed Representations of Sentences and Documents, PDF, github-code1, github-code2 {Paragraph Vectors, 2014}

  • Skip-Thoughts Vectors github code {Skip-Thpughts vectors, 2015}

  • Learning Distributed Representations of Sentences from Unlabelled Data arxiv, github {SDAE, Fast}

CNN classification

  • A Convolutional Neural Network for Modelling Sentences, PDF ACL 2014. Nal Kalchbrenner, Edward Grefenstette and Phil Blunsom. [convnet for sentences, dynamic, k-max pooling, stacked ]

  • Convolutional Neural Networks for Sentence Classification, arxiv : 2014. Kim, Yoon. [code -theano ,code - keras] [convnet for sentences]

  • Convolutional Neural Network Architectures for Matching Natural Language Sentences, pdf NIPS 2014, Baotian Hu, Zhengdong Lu, Hang Li, etc. [sentence matching, ARC-I, ARC-II]

  • Relation Classification via Convolutional Deep Neural Network“, PDF COLING 2014,Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou and Jun Zhao [Relation Classification, word feature, Position feature ]

  • Effective Use ofWord Order for Text Categorization with Convolutional Neural Networks, arXiv 2014, Rie Johnson, Tong Zhang . [Text categorization, Word Order,seq-CNN for text, bow-CNN for text, parallel CNN ]

  • Character-level Convolutional Networks for Text Classification, arxiv NIPS 2015, {character-level CNN}

  • Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding, PDF NIPS 2015, Rie Johnson, Tong Zhang

  • Recurrent Convolutional Neural Networks for Text ClassificationLINK AAAI2015, (RCNN)

  • The Forest Convolutional Network: Compositional Distributional Semantics with a Neural Chart and without Binarization, pdf EMNLP 2015, Phong Le and Willem Zuidema. [Tree CNN ]

LSTM

  • Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings, Rie Johnson, Tong Zhang PDF ICML 2016 [one hot LSTM]