no code implementations • EACL 2021 • Andrey Kutuzov, Elizaveta Kuzmenko
We describe a new addition to the WebVectors toolkit which is used to serve word embedding models over the Web.
no code implementations • WS 2019 • Andrey Kutuzov, Elizaveta Kuzmenko
Then, these models were evaluated on the word sense disambiguation task.
1 code implementation • ACL 2019 • Yi-Ling Chung, Elizaveta Kuzmenko, Serra Sinem Tekiroglu, Marco Guerini
Although there is an unprecedented effort to provide adequate responses in terms of laws and policies to hate content on social media platforms, dealing with hatred online is still a tough problem.
no code implementations • WS 2019 • Elizaveta Kuzmenko, Aur{\'e}lie Herbelot
There are two main aspects to this difference: a) DSMs are built over corpus data which may or may not reflect {`}what is in the world{'}; b) they are built from word co-occurrences, that is, from lexical types rather than entities and sets.
no code implementations • EACL 2017 • Andrey Kutuzov, Elizaveta Kuzmenko
In this demo we present WebVectors, a free and open-source toolkit helping to deploy web services which demonstrate and visualize distributional semantic models (widely known as word embeddings).
no code implementations • WS 2017 • Andrey Kutuzov, Elizaveta Kuzmenko, Lidia Pivovarova
This paper presents a method of automatic construction extraction from a large corpus of Russian.
1 code implementation • WS 2016 • Andrey Kutuzov, Elizaveta Kuzmenko, Anna Marakasova
We present an approach to detect differences in lexical semantics across English language registers, using word embedding models from distributional semantics paradigm.
no code implementations • LREC 2016 • Andrey Kutuzov, Elizaveta Kuzmenko
In this paper, a new approach towards semantic clustering of the results of ambiguous search queries is presented.