Papers and Book to look at when starting NLP. I will continue to update the content!! 🚀
mathematics | machine learning |
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mathematics for machine learning | Pattern Recognition and Machine Learning |
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[2013/01] Efficient Estimation of Word Representations in Vector Space
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[2014/12] Dependency-Based Word Embeddings
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[2015/07] Neural Machine Translation of Rare Words with Subword Units
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[2014/07] GloVe: Global Vectors for Word Representation : GloVe
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[2016/06] Siamese CBOW: Optimizing Word Embeddings for Sentence Representations : Siamese CBOW
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[2016/07] Enriching Word Vectors with Subword Information : fastText
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[2014/09] Sequence to Sequence Learningwith Neural Networks : seq2seq
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[2017/07] Attention Is All You Need : Transformer
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[2017/08] Learned in Translation: Contextualized Word Vectors : CoVe
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[2018/01]Universal Language Model Fine-tuning for Text Classification : ULMFIT
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[2018/02] Deep contextualized word representations : ELMo
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[2018/06] Improving Language Understanding by Generative Pre-Training : GPT-1
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[2018/10] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding : BERT
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[2019/02] Language Models are Unsupervised Multitask Learners : GPT-2
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[2019/04] Language Models with Transformers
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[2019/01] Cross-lingual Language Model Pretraining XLM
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[2019/01] Multi-Task Deep Neural Networks for Natural Language Understanding : MT-DNN
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[2019/01] Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context : Transformer-XL
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[2019/06] XLNet: Generalized Autoregressive Pretraining for Language Understanding : XLNet
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[2019/09] Fine-Tuning Language Models from Human Preferences
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[2019/01] BioBERT: a pre-trained biomedical language representation model for biomedical text mining : BioBERT
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[2019/03] SciBERT: A Pretrained Language Model for Scientific Text : SciBERT
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[2019/04] ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission : ClinicalBERT
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[2019/06] HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization : HIBERT
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[2019/07] SpanBERT: Improving Pre-training by Representing and Predicting Spans : SpanBERT
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[2019/08] Pre-Training with Whole Word Masking for Chinese BERT
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[2019/07] R-Transformer: Recurrent Neural Network Enhanced Transformer : R-Transformer
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[2019/09] FREELB: ENHANCED ADVERSARIAL TRAINING FOR LANGUAGE UNDERSTANDING : FREELB
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[2019/09] Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
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[2018/07] Subword-level Word Vector Representations for Korean