├── .gitignore ├── A Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summaries.md ├── A Simple but Tough-to-Beat Baseline for Sentence Embeddings.md ├── Achieving Human Parity on Automatic Chinese to English News Translation.md ├── An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modelling.md ├── An Exploration of Neural Sequence-to-Sequence Architectures for Automatic Post-Editing.md ├── Comparative Study of CNN and RNN for Natural Language Processing.md ├── Deep contextualized word representations.md ├── Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer.md ├── Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change.md ├── Do Neural Network Cross-Modal Mappings Really Bridge Modalities.md ├── Dynamic Word Embeddings for Evolving Semantic Discovery.md ├── Generating Wikipedia by Summarizing Long Sentences.md ├── Incorporating Copying Mechanism in Sequence-to-Sequence Learning.md ├── Learned in Translation: Contextualized Word Vectors.md ├── Learning to Ask: Neural Question Generation for Reading Comprehension.md ├── Learning to generate one-sentence biographies from Wikidata.md ├── Morphological Inflection Generation with Hard Monotonic Attention.md ├── Neural Networks For Negation Scope Detection.md ├── Neural Text Generation from Structured Data with Application to the Biography Domain.md ├── Offline Bilingual Word Vectors, Orthogonal Transformations and the Inverted Softmax.md ├── Pointer Networks.md ├── Polyglot-NER Massive Multilingual Named Entity Recognition.md ├── README.md ├── Semantically Equivalent Adversarial Rules for Debugging NLP models.md ├── Seq2SQL: Generating Structured Queries from Natural Language Using Reinforcement Learning.md ├── Supervised Learning of Universal Sentence Representations from Natural Language Inference Data.md ├── The Importance of Being Recurrent for Modeling Hierarchical Structure.md ├── The Natural Language Decathlon: Multitask Learning as Question Answering.md ├── Universal Language Model Fine-tuning for Text Classification.md ├── Universal Sentence Encoder.md ├── Word Translation without Parallel Data.md └── figures ├── copynet.png ├── dynamic_word_embeddings.png ├── semantic_shift.png └── tcn.png /.gitignore: -------------------------------------------------------------------------------- 1 | .idea/ 2 | -------------------------------------------------------------------------------- /A Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summaries.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/A Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summaries.md -------------------------------------------------------------------------------- /A Simple but Tough-to-Beat Baseline for Sentence Embeddings.md: 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Sequence-to-Sequence Learning.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Incorporating Copying Mechanism in Sequence-to-Sequence Learning.md -------------------------------------------------------------------------------- /Learned in Translation: Contextualized Word Vectors.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Learned in Translation: Contextualized Word Vectors.md -------------------------------------------------------------------------------- /Learning to Ask: Neural Question Generation for Reading Comprehension.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Learning to Ask: Neural Question Generation for Reading Comprehension.md -------------------------------------------------------------------------------- /Learning to generate one-sentence biographies from Wikidata.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Learning to generate one-sentence biographies from Wikidata.md -------------------------------------------------------------------------------- /Morphological Inflection Generation with Hard Monotonic Attention.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Morphological Inflection Generation with Hard Monotonic Attention.md -------------------------------------------------------------------------------- /Neural Networks For Negation Scope Detection.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Neural Networks For Negation Scope Detection.md -------------------------------------------------------------------------------- /Neural Text Generation from Structured Data with Application to the Biography Domain.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Neural Text Generation from Structured Data with Application to the Biography Domain.md -------------------------------------------------------------------------------- /Offline Bilingual Word Vectors, Orthogonal Transformations and the Inverted Softmax.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Offline Bilingual Word Vectors, Orthogonal Transformations and the Inverted Softmax.md -------------------------------------------------------------------------------- /Pointer Networks.md: 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https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Semantically Equivalent Adversarial Rules for Debugging NLP models.md -------------------------------------------------------------------------------- /Seq2SQL: Generating Structured Queries from Natural Language Using Reinforcement Learning.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Seq2SQL: Generating Structured Queries from Natural Language Using Reinforcement Learning.md -------------------------------------------------------------------------------- /Supervised Learning of Universal Sentence Representations from Natural Language Inference Data.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Supervised Learning of Universal Sentence Representations from Natural Language Inference Data.md 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https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Universal Language Model Fine-tuning for Text Classification.md -------------------------------------------------------------------------------- /Universal Sentence Encoder.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Universal Sentence Encoder.md -------------------------------------------------------------------------------- /Word Translation without Parallel Data.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/Word Translation without Parallel Data.md -------------------------------------------------------------------------------- /figures/copynet.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/nlptown/nlppapers/HEAD/figures/copynet.png 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