Dynamic Meta-Embeddings for Improved Sentence Representations

Code

• github.com/facebookresearch/DME
  Officialpytorch★ 0
• github.com/ellerypan/QUORA-INSINCERE-QUESTION-CLASSIFICATION
  none★ 0
• github.com/kushalchauhan98/dynamic-meta-embeddings
  pytorch★ 0

Abstract

While one of the first steps in many NLP systems is selecting what pre-trained word embeddings to use, we argue that such a step is better left for neural networks to figure out by themselves. To that end, we introduce dynamic meta-embeddings, a simple yet effective method for the supervised learning of embedding ensembles, which leads to state-of-the-art performance within the same model class on a variety of tasks. We subsequently show how the technique can be used to shed new light on the usage of word embeddings in NLP systems.

Tasks

Benchmark Results

Reproductions