no code implementations • EACL (WANLP) 2021 • Abraham Israeli, Yotam Nahum, Shai Fine, Kfir Bar
In this paper we present designated solutions for sentiment classification and sarcasm detection tasks that were introduced as part of a shared task by Abu Farha et al. (2021).
no code implementations • LChange (ACL) 2022 • Anat Samohi, Daniel Weisberg Mitelman, Kfir Bar
This model has been considered as a method of describing genetic relationships between languages.
no code implementations • NAACL (CLPsych) 2022 • Yaara Shriki, Ido Ziv, Nachum Dershowitz, Eiran Harel, Kfir Bar
Natural language processing tools have been shown to be effective for detecting symptoms of schizophrenia in transcribed speech.
no code implementations • 25 Feb 2024 • Aviad Rom, Kfir Bar
We train a bilingual Arabic-Hebrew language model using a transliterated version of Arabic texts in Hebrew, to ensure both languages are represented in the same script.
no code implementations • ICNLSP 2021 • Aviad Rom, Kfir Bar
We observe a recent behaviour on social media, in which users intentionally remove consonantal dots from Arabic letters, in order to bypass content-classification algorithms.
no code implementations • 6 Oct 2020 • Kfir Bar, Nachum Dershowitz, Lena Dankin
We suggest a model for metaphor interpretation using word embeddings trained over a relatively large corpus.
no code implementations • COLING (WANLP) 2020 • Ori Terner, Kfir Bar, Nachum Dershowitz
To measure the contribution of context to learning, we also tested word-shuffled data, for which the error rises to 2. 5%.
no code implementations • WS 2019 • Kfir Bar, Vered Zilberstein, Ido Ziv, Heli Baram, Nachum Dershowitz, Samuel Itzikowitz, Eiran Vadim Harel
Natural language processing tools are used to automatically detect disturbances in transcribed speech of schizophrenia inpatients who speak Hebrew.