Natural Language Processing

NLP Comments

Core Concepts

  1. Adam Optimizer
  2. SHA-RNN
  4. T-SNE
  5. Adam Optimizer
  6. SentencePiece
  7. Byte Pair Encoding

Beyond Word Vectors

  1. Deep Averaging Networks
  2. BERT
  3. Structured self attentive sentence embedding


  1. Hierarchical Attention Networks
  2. Easy Data Augmentation
  3. CNN Document Classification

Named Entity Recognition & Slot Filling

  1. SUTIME: A Library for Recognizing and Normalizing Time Expressions
  2. Named Entity Recognition with Bidirectional LSTM-CNNs
  3. Pangloss
  4. OntoNotes 5
  5. Entity Linking with a KB
  6. Pangloss

Conversational AI and NLU

  1. Dialog State Tracking: A Neural Reading Comprehension Approach
  2. Scalable Multi-Domain Dialogue State Tracking
  3. Dialog Context Language Modeling with Recurrent Neural Networks
  4. Effective Incorporation of Speaker Information in Utterance Encoding in Dialog
  5. Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
  6. Conversational Recommender System
  7. Learning End2End Goal Oriented Dialog

Machine Reading Comprehension

  1. BiDirectional Attention Flow
  2. Dynamic Co-attention Networks

Natural Language Generation (NLG)

  1. Attention Is All You Need
  2. Blockwise Parallel Decoding for Deep Autoregressive Models
  3. Gmail Smart Compose: Real-Time Assisted Writing
  4. GPT2
  5. DialoGPT
  6. CTRL
  7. Grammar Correction Corpora
  8. Get To the Point
  9. Gensim summarization
  10. Smart Reply
  11. Intent to Code Generation
  12. Pegasus
  13. BART
  14. Personalized GEC

Kaushik Rangadurai

Code. Learn. Explore

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