Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Toledo, Assaf"'
Autor:
Yehudai, Asaf, Carmeli, Boaz, Mass, Yosi, Arviv, Ofir, Mills, Nathaniel, Toledo, Assaf, Shnarch, Eyal, Choshen, Leshem
The lack of high-quality data for content-grounded generation tasks has been identified as a major obstacle to advancing these tasks. To address this gap, we propose Genie, a novel method for automatically generating high-quality content-grounded dat
Externí odkaz:
http://arxiv.org/abs/2401.14367
Autor:
Gretz, Shai, Toledo, Assaf, Friedman, Roni, Lahav, Dan, Weeks, Rose, Bar-Zeev, Naor, Sedoc, João, Sangha, Pooja, Katz, Yoav, Slonim, Noam
The COVID-19 pandemic has made a huge global impact and cost millions of lives. As COVID-19 vaccines were rolled out, they were quickly met with widespread hesitancy. To address the concerns of hesitant people, we launched VIRA, a public dialogue sys
Externí odkaz:
http://arxiv.org/abs/2205.11966
Autor:
Friedman, Roni, Sedoc, João, Gretz, Shai, Toledo, Assaf, Weeks, Rose, Bar-Zeev, Naor, Katz, Yoav, Slonim, Noam
Public trust in medical information is crucial for successful application of public health policies such as vaccine uptake. This is especially true when the information is offered remotely, by chatbots, which have become increasingly popular in recen
Externí odkaz:
http://arxiv.org/abs/2205.12240
Autor:
Orbach, Matan, Bilu, Yonatan, Toledo, Assaf, Lahav, Dan, Jacovi, Michal, Aharonov, Ranit, Slonim, Noam
An educated and informed consumption of media content has become a challenge in modern times. With the shift from traditional news outlets to social media and similar venues, a major concern is that readers are becoming encapsulated in "echo chambers
Externí odkaz:
http://arxiv.org/abs/2005.01157
Autor:
Gretz, Shai, Friedman, Roni, Cohen-Karlik, Edo, Toledo, Assaf, Lahav, Dan, Aharonov, Ranit, Slonim, Noam
Identifying the quality of free-text arguments has become an important task in the rapidly expanding field of computational argumentation. In this work, we explore the challenging task of argument quality ranking. To this end, we created a corpus of
Externí odkaz:
http://arxiv.org/abs/1911.11408
Autor:
Toledo, Assaf, Gretz, Shai, Cohen-Karlik, Edo, Friedman, Roni, Venezian, Elad, Lahav, Dan, Jacovi, Michal, Aharonov, Ranit, Slonim, Noam
We explore the task of automatic assessment of argument quality. To that end, we actively collected 6.3k arguments, more than a factor of five compared to previously examined data. Each argument was explicitly and carefully annotated for its quality.
Externí odkaz:
http://arxiv.org/abs/1909.01007
Autor:
Kantor, Yoav, Katz, Yoav, Choshen, Leshem, Cohen-Karlik, Edo, Liberman, Naftali, Toledo, Assaf, Menczel, Amir, Slonim, Noam
The field of Grammatical Error Correction (GEC) has produced various systems to deal with focused phenomena or general text editing. We propose an automatic way to combine black-box systems. Our method automatically detects the strength of a system o
Externí odkaz:
http://arxiv.org/abs/1906.03897
Nearest neighbors in word embedding models are commonly observed to be semantically similar, but the relations between them can vary greatly. We investigate the extent to which word embedding models preserve syntactic interchangeability, as reflected
Externí odkaz:
http://arxiv.org/abs/1904.00669
Autor:
Toledo, Assaf1 (AUTHOR) assaf.toledo@ibm.com, Venezian, Elad1 (AUTHOR), Slonim, Noam1 (AUTHOR) assaf.toledo@ibm.com
Publikováno v:
Entropy. Aug2022, Vol. 24 Issue 8, p1132-N.PAG. 15p.
Akademický článek
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