Deep Contextualized Word Representations
Matthew E. Peters, Mark E Neumann low, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, Luke Zettlemoyer
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, Luke Zettlemoyer. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). 2018.
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- DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter→Deep Contextualized Word RepresentationsLegacy edge — source detail unavailable
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer→Deep Contextualized Word RepresentationsLegacy edge — source detail unavailable
- HuggingFace's Transformers: State-of-the-art Natural Language Processing→Deep Contextualized Word RepresentationsLegacy edge — source detail unavailable
- BERTScore: Evaluating Text Generation with BERT→Deep Contextualized Word RepresentationsLegacy edge — source detail unavailable
- XLNet: Generalized Autoregressive Pretraining for Language Understanding→Deep Contextualized Word RepresentationsLegacy edge — source detail unavailable
- Unsupervised Data Augmentation for Consistency Training→Deep Contextualized Word RepresentationsLegacy edge — source detail unavailable
- Deep Learning Enabled Semantic Communication Systems→Deep Contextualized Word RepresentationsLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→Long Short-Term MemoryLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Deep Contextualized Word Representations→Dropout: a simple way to prevent neural networks from overfittingLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→Glove: Global Vectors for Word RepresentationLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence DataLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→Enriching Word Vectors with Subword InformationLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→Building a Large Annotated Corpus of English: The Penn TreebankLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→Recursive Deep Models for Semantic Compositionality Over a Sentiment TreebankLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→ADADELTA: An Adaptive Learning Rate MethodLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→Neural Architectures for Named Entity RecognitionLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→Natural Language Processing (almost) from ScratchLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→The Proposition Bank: An Annotated Corpus of Semantic RolesLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→Word Representations: A Simple and General Method for Semi-Supervised LearningLegacy edge — source detail unavailable
- Deep Contextualized Word Representations→An Empirical Exploration of Recurrent Network ArchitecturesLegacy edge — source detail unavailable
- The Proposition Bank: An Annotated Corpus of Semantic Roles→Building a Large Annotated Corpus of English: The Penn TreebankLegacy edge — source detail unavailable
- Glove: Global Vectors for Word Representation→Word Representations: A Simple and General Method for Semi-Supervised LearningLegacy edge — source detail unavailable
- Neural Architectures for Named Entity Recognition→Long Short-Term MemoryLegacy edge — source detail unavailable
- Neural Architectures for Named Entity Recognition→Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence DataLegacy edge — source detail unavailable
- Neural Architectures for Named Entity Recognition→Word Representations: A Simple and General Method for Semi-Supervised LearningLegacy edge — source detail unavailable
- Neural Architectures for Named Entity Recognition→Natural Language Processing (almost) from ScratchLegacy edge — source detail unavailable
- Neural Architectures for Named Entity Recognition→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Neural Architectures for Named Entity Recognition→ADADELTA: An Adaptive Learning Rate MethodLegacy edge — source detail unavailable
- BERTScore: Evaluating Text Generation with BERT→Glove: Global Vectors for Word RepresentationLegacy edge — source detail unavailable
- BERTScore: Evaluating Text Generation with BERT→XLNet: Generalized Autoregressive Pretraining for Language UnderstandingLegacy edge — source detail unavailable
- XLNet: Generalized Autoregressive Pretraining for Language Understanding→Unsupervised Data Augmentation for Consistency TrainingLegacy edge — source detail unavailable
- Natural Language Processing (almost) from Scratch→Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence DataLegacy edge — source detail unavailable
- Natural Language Processing (almost) from Scratch→Word Representations: A Simple and General Method for Semi-Supervised LearningLegacy edge — source detail unavailable
- Natural Language Processing (almost) from Scratch→The Proposition Bank: An Annotated Corpus of Semantic RolesLegacy edge — source detail unavailable
- Unsupervised Data Augmentation for Consistency Training→Glove: Global Vectors for Word RepresentationLegacy edge — source detail unavailable
- HuggingFace's Transformers: State-of-the-art Natural Language Processing→DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterLegacy edge — source detail unavailable
- HuggingFace's Transformers: State-of-the-art Natural Language Processing→Exploring the Limits of Transfer Learning with a Unified Text-to-Text TransformerLegacy edge — source detail unavailable
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer→Dropout: a simple way to prevent neural networks from overfittingLegacy edge — source detail unavailable
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer→Glove: Global Vectors for Word RepresentationLegacy edge — source detail unavailable
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer→Recursive Deep Models for Semantic Compositionality Over a Sentiment TreebankLegacy edge — source detail unavailable
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer→XLNet: Generalized Autoregressive Pretraining for Language UnderstandingLegacy edge — source detail unavailable
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer→DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterLegacy edge — source detail unavailable
- An Empirical Exploration of Recurrent Network Architectures→Building a Large Annotated Corpus of English: The Penn TreebankLegacy edge — source detail unavailable
- An Empirical Exploration of Recurrent Network Architectures→Long Short-Term MemoryLegacy edge — source detail unavailable
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| Topic Modeling | Computer Science |
| Natural Language Processing Techniques | Computer Science |
| Sentiment Analysis and Opinion Mining | Computer Science |
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