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        <title>Dynamic Meta-Embeddings for Improved Sentence Representations</title>
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        <namePart type="given">Douwe</namePart>
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        <namePart type="given">Changhan</namePart>
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    <name type="personal">
        <namePart type="given">Kyunghyun</namePart>
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            <title>Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing</title>
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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.</abstract>
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    <identifier type="doi">10.18653/v1/D18-1176</identifier>
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%0 Conference Proceedings
%T Dynamic Meta-Embeddings for Improved Sentence Representations
%A Kiela, Douwe
%A Wang, Changhan
%A Cho, Kyunghyun
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F kiela-etal-2018-dynamic
%X 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.
%R 10.18653/v1/D18-1176
%U https://aclanthology.org/D18-1176
%U https://doi.org/10.18653/v1/D18-1176
%P 1466-1477

Markdown (Informal)

[Dynamic Meta-Embeddings for Improved Sentence Representations](https://aclanthology.org/D18-1176) (Kiela et al., EMNLP 2018)

• Dynamic Meta-Embeddings for Improved Sentence Representations (Kiela et al., EMNLP 2018)

ACL

• Douwe Kiela, Changhan Wang, and Kyunghyun Cho. 2018. Dynamic Meta-Embeddings for Improved Sentence Representations. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 1466–1477, Brussels, Belgium. Association for Computational Linguistics.