@inproceedings{kutuzov-kuzmenko-2021-representing,
title = "Representing {ELM}o embeddings as two-dimensional text online",
author = "Kutuzov, Andrey and
Kuzmenko, Elizaveta",
editor = "Gkatzia, Dimitra and
Seddah, Djam{\'e}",
booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.eacl-demos.18",
doi = "10.18653/v1/2021.eacl-demos.18",
pages = "143--148",
abstract = "We describe a new addition to the WebVectors toolkit which is used to serve word embedding models over the Web. The new ELMoViz module adds support for contextualized embedding architectures, in particular for ELMo models. The provided visualizations follow the metaphor of {`}two-dimensional text{'} by showing lexical substitutes: words which are most semantically similar in context to the words of the input sentence. The system allows the user to change the ELMo layers from which token embeddings are inferred. It also conveys corpus information about the query words and their lexical substitutes (namely their frequency tiers and parts of speech). The module is well integrated into the rest of the WebVectors toolkit, providing lexical hyperlinks to word representations in static embedding models. Two web services have already implemented the new functionality with pre-trained ELMo models for Russian, Norwegian and English.",
}
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<abstract>We describe a new addition to the WebVectors toolkit which is used to serve word embedding models over the Web. The new ELMoViz module adds support for contextualized embedding architectures, in particular for ELMo models. The provided visualizations follow the metaphor of ‘two-dimensional text’ by showing lexical substitutes: words which are most semantically similar in context to the words of the input sentence. The system allows the user to change the ELMo layers from which token embeddings are inferred. It also conveys corpus information about the query words and their lexical substitutes (namely their frequency tiers and parts of speech). The module is well integrated into the rest of the WebVectors toolkit, providing lexical hyperlinks to word representations in static embedding models. Two web services have already implemented the new functionality with pre-trained ELMo models for Russian, Norwegian and English.</abstract>
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%0 Conference Proceedings
%T Representing ELMo embeddings as two-dimensional text online
%A Kutuzov, Andrey
%A Kuzmenko, Elizaveta
%Y Gkatzia, Dimitra
%Y Seddah, Djamé
%S Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F kutuzov-kuzmenko-2021-representing
%X We describe a new addition to the WebVectors toolkit which is used to serve word embedding models over the Web. The new ELMoViz module adds support for contextualized embedding architectures, in particular for ELMo models. The provided visualizations follow the metaphor of ‘two-dimensional text’ by showing lexical substitutes: words which are most semantically similar in context to the words of the input sentence. The system allows the user to change the ELMo layers from which token embeddings are inferred. It also conveys corpus information about the query words and their lexical substitutes (namely their frequency tiers and parts of speech). The module is well integrated into the rest of the WebVectors toolkit, providing lexical hyperlinks to word representations in static embedding models. Two web services have already implemented the new functionality with pre-trained ELMo models for Russian, Norwegian and English.
%R 10.18653/v1/2021.eacl-demos.18
%U https://aclanthology.org/2021.eacl-demos.18
%U https://doi.org/10.18653/v1/2021.eacl-demos.18
%P 143-148
Markdown (Informal)
[Representing ELMo embeddings as two-dimensional text online](https://aclanthology.org/2021.eacl-demos.18) (Kutuzov & Kuzmenko, EACL 2021)
ACL
- Andrey Kutuzov and Elizaveta Kuzmenko. 2021. Representing ELMo embeddings as two-dimensional text online. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 143–148, Online. Association for Computational Linguistics.