Gamal Crichton

Attending to Characters in Neural Sequence Labeling Models

2016 · arXiv (Cornell University)

Sequence labeling architectures use word embeddings for capturing similarity, but suffer when handling previously unseen or rare words. We investigate character-level extensions to such models and propose a novel architecture for combining alternative word representations. …

How to Train good Word Embeddings for Biomedical NLP

2016

The quality of word embeddings depends on the input corpora, model architectures, and hyper-parameter settings. Using the state-of-the-art neural embedding tool word2vec and both intrinsic and extrinsic evaluations, we present a comprehensive study of how …