Search Results for author: Shai Gretz

Found 10 papers, 2 papers with code

VIRATrustData: A Trust-Annotated Corpus of Human-Chatbot Conversations About COVID-19 Vaccines

no code implementations24 May 2022 Roni Friedman, João Sedoc, Shai Gretz, Assaf Toledo, Rose Weeks, Naor Bar-Zeev, Yoav Katz, Noam Slonim

Public trust in medical information is crucial for successful application of public health policies such as vaccine uptake.

Chatbot

The workweek is the best time to start a family -- A Study of GPT-2 Based Claim Generation

no code implementations Findings of the Association for Computational Linguistics 2020 Shai Gretz, Yonatan Bilu, Edo Cohen-Karlik, Noam Slonim

Argument generation is a challenging task whose research is timely considering its potential impact on social media and the dissemination of information.

Retrieval

What if we had no Wikipedia? Domain-independent Term Extraction from a Large News Corpus

no code implementations17 Sep 2020 Yonatan Bilu, Shai Gretz, Edo Cohen, Noam Slonim

One of the most impressive human endeavors of the past two decades is the collection and categorization of human knowledge in the free and accessible format that is Wikipedia.

Term Extraction

A Large-scale Dataset for Argument Quality Ranking: Construction and Analysis

2 code implementations26 Nov 2019 Shai Gretz, Roni Friedman, Edo Cohen-Karlik, Assaf Toledo, Dan Lahav, Ranit Aharonov, Noam Slonim

To this end, we created a corpus of 30, 497 arguments carefully annotated for point-wise quality, released as part of this work.

Automatic Argument Quality Assessment -- New Datasets and Methods

no code implementations3 Sep 2019 Assaf Toledo, Shai Gretz, Edo Cohen-Karlik, Roni Friedman, Elad Venezian, Dan Lahav, Michal Jacovi, Ranit Aharonov, Noam Slonim

In spite of the inherent subjective nature of the task, both annotation schemes led to surprisingly consistent results.

Language Modelling

Towards Effective Rebuttal: Listening Comprehension using Corpus-Wide Claim Mining

no code implementations WS 2019 Tamar Lavee, Matan Orbach, Lili Kotlerman, Yoav Kantor, Shai Gretz, Lena Dankin, Shachar Mirkin, Michal Jacovi, Yonatan Bilu, Ranit Aharonov, Noam Slonim

To this end, we collected a large dataset of $400$ speeches in English discussing $200$ controversial topics, mined claims for each topic, and asked annotators to identify the mined claims mentioned in each speech.

Towards an argumentative content search engine using weak supervision

no code implementations COLING 2018 Ran Levy, Ben Bogin, Shai Gretz, Ranit Aharonov, Noam Slonim

Our results clearly indicate that the system is able to successfully generalize from the weak signal, outperforming previously reported results in terms of both precision and coverage.

Argument Mining Decision Making

Unsupervised corpus--wide claim detection

no code implementations WS 2017 Ran Levy, Shai Gretz, Benjamin Sznajder, Shay Hummel, Ranit Aharonov, Noam Slonim

Automatic claim detection is a fundamental argument mining task that aims to automatically mine claims regarding a topic of consideration.

Argument Mining Decision Making

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