Dynamic Meta-Embeddings for Improved Sentence Representations

Douwe Kiela; Changhan Wang; Kyunghyun Cho

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arXiv · 1804.07983

Dynamic Meta-Embeddings for Improved Sentence Representations

Douwe Kiela·Changhan Wang·Kyunghyun Cho

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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.

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Douwe Kiela, Changhan Wang, Kyunghyun Cho. 2018-04-21. Dynamic Meta-Embeddings for Improved Sentence Representations. https://arxiv.org/abs/1804.07983

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