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Awesome-NLP-Resources

This repository contains landmark research papers in Natural Language Processing that came out in this century.
https://github.com/Robofied/Awesome-NLP-Resources

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Awesome NLP Resources
- ![Awesome - NLP-Resources)
- ![Maintenance - NLP-Resources/graphs/commit-activity) [![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)
How to Read a Paper? :page_with_curl:
List of Research Papers
- Machine Translation
  - Understanding Back-Translation at Scale
  - MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning
  - Scaling Neural Machine Translation
  - The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation
  - Convolutional Sequence to Sequence Learning - Modified Attention model with convolutional layer
  - Learning Phase Representations using RNN Encoder-Decoder for statistical Machine Translation
  - Attention Model(Neural Machine Translation By Jointly learning to Align and Translate) - Attention model architecture modified version for encoder decoder models (Don't confuse with [<i><b>Attention is all you need</b> paper</i>](#Transformers) i.e, for transformers concept)
  - Understanding Back-Translation at Scale
- Language Models
  - Scalable Hierarchical Distributed Language Model
  - Bag of Tricks for Efficient Text Classification - fastText(by Facebook AI Research) trained on billion of words for text classification.
  - Language Models are Unsupervised Multitask Learners
  - Hierarchical Probabilistic Neural Network Language Model - Speed up training and recogintion(by 200) - Yoshua Bengio
  - Bag of Tricks for Efficient Text Classification - fastText(by Facebook AI Research) trained on billion of words for text classification.
- Word Embeddings
  - Distributed Representations of Sentences and Documents - Sentence/Document to vectors by Tomas Mikolov by Google
  - Deep contextualized word representations - based on deep birectional Language Model by Allen Institute for Artificial Intelligence
  - Enriching Word Vectors with Subword Information - Handles morphology and generates vectors for words not present in training dataset by Facebook AI Research <img src="fb-icon.png" width="20" height="20">
  - Misspelling Oblivious Word Embeddings
  - Efficient Estimation of Word Representations in Vector Space - High quality vector representation from huge data sets by Tomas Mikolov(Google)
  - Deep contextualized word representations - based on deep birectional Language Model by Allen Institute for Artificial Intelligence
  - Enriching Word Vectors with Subword Information - Handles morphology and generates vectors for words not present in training dataset by Facebook AI Research <img src="fb-icon.png" width="20" height="20">
- Image to Text
  - Neural Image Caption Generation with Visual Attention
  - Deep Visual-Semantic Alignments for Generating Image Descriptions
- Transformers
  - Attention Is All You Need
  - BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding - Multimodal Recurrent Neural Network architecture for image description by [Andrej Kaparthy <img src="andreaj.svg" width="20" height="20"> ](http://karpathy.github.io/) and Le-Fei-fei
List of blogs
- Machine Translation
- Image to Text
- Transformers
  - The Illustrated Transformer - Transformers Research paper core details explained by [Jalammar](http://jalammar.github.io/)
  - The Illustrated BERT - BERT is explained by [Jalammar](http://jalammar.github.io/)
  - A Visual Guide to Using BERT for the First Time :boom: - Very beautifully explained BERT architecture with the help of visuals.

Categories

List of blogs 59 List of Research Papers 24 How to Read a Paper? :page_with_curl: 4 Awesome NLP Resources 2

Sub Categories

Image to Text 55 Machine Translation 11 Word Embeddings 7 Language Models 5 Transformers 5