atural Language Processing - Referenced Papers

MT-DNN: https://arxiv.org/pdf/1901.11504.pdf

Graph-Embedding: https://arxiv.org/pdf/1905.02138.pdf

Transformer-XL: https://arxiv.org/pdf/1901.02860.pdf

Math-Trafo: https://arxiv.org/pdf/1812.02825.pdf

GPT-2: https://s3-us-west-2.amazonaws.com/openai-assets/research-covers/language-unsupervised/language_understanding_paper.pdf

GPT: https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf

BERT: https://arxiv.org/pdf/1810.04805.pdf

Universal: https://arxiv.org/pdf/1803.11175.pdf

UnivTrans: https://arxiv.org/pdf/1807.03819.pdf

Graph-Attention: https://papers.nips.cc/paper/8131-watch-your-step-learning-node-embeddings-via-graph-attention.pdf

Transformer: https://arxiv.org/pdf/1706.03762.pdf

BeamSearch: https://arxiv.org/pdf/1702.01806.pdf

NMT: https://arxiv.org/pdf/1609.08144.pdf

DeepWalk: http://www.perozzi.net/publications/14_kdd_deepwalk.pdf