Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Bareket, Dan"'
Publikováno v:
In Proceedings of EACL 2023, 849-864 (2023)
Semitic morphologically-rich languages (MRLs) are characterized by extreme word ambiguity. Because most vowels are omitted in standard texts, many of the words are homographs with multiple possible analyses, each with a different pronunciation and di
Externí odkaz:
http://arxiv.org/abs/2405.07099
We develop computational models to analyze court statements in order to assess judicial attitudes toward victims of sexual violence in the Israeli court system. The study examines the resonance of "rape myths" in the criminal justice system's respons
Externí odkaz:
http://arxiv.org/abs/2305.05302
Autor:
Gueta, Eylon, Shmidman, Avi, Shmidman, Shaltiel, Shmidman, Cheyn Shmuel, Guedalia, Joshua, Koppel, Moshe, Bareket, Dan, Seker, Amit, Tsarfaty, Reut
We present a new pre-trained language model (PLM) for modern Hebrew, termed AlephBERTGimmel, which employs a much larger vocabulary (128K items) than standard Hebrew PLMs before. We perform a contrastive analysis of this model against all previous He
Externí odkaz:
http://arxiv.org/abs/2211.15199
Autor:
Seker, Amit, Bandel, Elron, Bareket, Dan, Brusilovsky, Idan, Greenfeld, Refael Shaked, Tsarfaty, Reut
Large Pre-trained Language Models (PLMs) have become ubiquitous in the development of language understanding technology and lie at the heart of many artificial intelligence advances. While advances reported for English using PLMs are unprecedented, r
Externí odkaz:
http://arxiv.org/abs/2104.04052
Autor:
Bareket, Dan, Tsarfaty, Reut
Named Entity Recognition (NER) is a fundamental NLP task, commonly formulated as classification over a sequence of tokens. Morphologically-Rich Languages (MRLs) pose a challenge to this basic formulation, as the boundaries of Named Entities do not ne
Externí odkaz:
http://arxiv.org/abs/2007.15620
It has been exactly a decade since the first establishment of SPMRL, a research initiative unifying multiple research efforts to address the peculiar challenges of Statistical Parsing for Morphologically-Rich Languages (MRLs).Here we reflect on parsi
Externí odkaz:
http://arxiv.org/abs/2005.01330
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.