Integrating Approaches to Word Representation
arXiv:2109.04876
Abstract
The problem of representing the atomic elements of language in modern neural learning systems is one of the central challenges of the field of natural language processing. I present a survey of the distributional, compositional, and relational approaches to addressing this task, and discuss various means of integrating them into systems, with special emphasis on the word level and the out-of-vocabulary phenomenon.
Adapted dissertation introduction
References in corpus (6)
- Natural Language Processing (almost) from Scratch
- ProjE: Embedding Projection for Knowledge Graph Completion
- CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters
- What to do about non-standard (or non-canonical) language in NLP
- Learning to Look Inside: Augmenting Token-Based Encoders with Character-Level Information
- Attending Form and Context to Generate Specialized Out-of-VocabularyWords Representations