Identifying and Investigating Unexpected Response to Treatment: A Diabetes Case Study. - Michal Ozery-Flato; Liat Ein-Dor; Naama Parush-Shear-Yashuv; Ranit Aharonov; Hani Neuvirth; Martin S. Kohn; Jianying Hu (Big Data, 2016)

Unsupervised corpus-wide claim detection. - Ran Levy 001; Shai Gretz; Benjamin Sznajder; Shay Hummel; Ranit Aharonov; Noam Slonim (ArgMining@EMNLP, 2017)

Learning Thematic Similarity Metric from Article Sections Using Triplet Networks. - Liat Ein-Dor; Yosi Mass; Alon Halfon; Elad Venezian; Ilya Shnayderman; Ranit Aharonov; Noam Slonim (ACL (2), 2018)

Will it Blend? Blending Weak and Strong Labeled Data in a Neural Network for Argumentation Mining. - Eyal Shnarch; Carlos Alzate; Lena Dankin; Martin Gleize; Yufang Hou 001; Leshem Choshen; Ranit Aharonov; Noam Slonim (ACL (2), 2018)

Towards an argumentative content search engine using weak supervision. - Ran Levy 001; Ben Bogin; Shai Gretz; Ranit Aharonov; Noam Slonim (COLING, 2018)

Learning Sentiment Composition from Sentiment Lexicons. - Orith Toledo-Ronen; Roy Bar-Haim; Alon Halfon; Charles Jochim; Amir Menczel; Ranit Aharonov; Noam Slonim (COLING, 2018)

Listening Comprehension over Argumentative Content. - Shachar Mirkin; Guy Moshkowich; Matan Orbach; Lili Kotlerman; Yoav Kantor; Tamar Lavee; Michal Jacovi; Yonatan Bilu; Ranit Aharonov; Noam Slonim (EMNLP, 2018)

Learning Concept Abstractness Using Weak Supervision. - Ella Rabinovich; Benjamin Sznajder; Artem Spector; Ilya Shnayderman; Ranit Aharonov; David Konopnicki; Noam Slonim (EMNLP, 2018)

From Surrogacy to Adoption; From Bitcoin to Cryptocurrency: Debate Topic Expansion. - Roy Bar-Haim; Dalia Krieger; Orith Toledo-Ronen; Lilach Edelstein; Yonatan Bilu; Alon Halfon; Yoav Katz; Amir Menczel; Ranit Aharonov; Noam Slonim (ACL (1), 2019)

Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network. - Martin Gleize; Eyal Shnarch; Leshem Choshen; Lena Dankin; Guy Moshkowich; Ranit Aharonov; Noam Slonim (ACL (1), 2019)

Towards Effective Rebuttal: Listening Comprehension Using Corpus-Wide Claim Mining. - Tamar Lavee; Matan Orbach; Lili Kotlerman; Yoav Kantor; Shai Gretz; Lena Dankin; Michal Jacovi; Yonatan Bilu; Ranit Aharonov; Noam Slonim (ArgMining@ACL, 2019)

A Dataset of General-Purpose Rebuttal. - Matan Orbach; Yonatan Bilu; Ariel Gera; Yoav Kantor; Lena Dankin; Tamar Lavee; Lili Kotlerman; Shachar Mirkin; Michal Jacovi; Ranit Aharonov; Noam Slonim (EMNLP/IJCNLP (1), 2019)

Automatic Argument Quality Assessment - New Datasets and Methods. - Assaf Toledo; Shai Gretz; Edo Cohen-Karlik; Roni Friedman; Elad Venezian; Dan Lahav; Michal Jacovi; Ranit Aharonov; Noam Slonim (EMNLP/IJCNLP (1), 2019)

Towards Effective Rebuttal: Listening Comprehension using Corpus-Wide Claim Mining. - Tamar Lavee; Matan Orbach; Lili Kotlerman; Yoav Kantor; Shai Gretz; Lena Dankin; Shachar Mirkin; Michal Jacovi; Yonatan Bilu; Ranit Aharonov; Noam Slonim (CoRR, 2019)

Fast End-to-End Wikification. - Ilya Shnayderman; Liat Ein-Dor; Yosi Mass; Alon Halfon; Benjamin Sznajder; Artem Spector; Yoav Katz; Dafna Sheinwald; Ranit Aharonov; Noam Slonim (CoRR, 2019)

Controversy in Context. - Benjamin Sznajder; Ariel Gera; Yonatan Bilu; Dafna Sheinwald; Ella Rabinovich; Ranit Aharonov; David Konopnicki; Noam Slonim (CoRR, 2019)

Corpus Wide Argument Mining - A Working Solution. - Liat Ein-Dor; Eyal Shnarch; Lena Dankin; Alon Halfon; Benjamin Sznajder; Ariel Gera; Carlos Alzate; Martin Gleize; Leshem Choshen; Yufang Hou 001; Yonatan Bilu; Ranit Aharonov; et al. (AAAI, 2020)

A Large-Scale Dataset for Argument Quality Ranking: Construction and Analysis. - Shai Gretz; Roni Friedman; Edo Cohen-Karlik; Assaf Toledo; Dan Lahav; Ranit Aharonov; Noam Slonim (AAAI, 2020)

Out of the Echo Chamber: Detecting Countering Debate Speeches. - Matan Orbach; Yonatan Bilu; Assaf Toledo; Dan Lahav; Michal Jacovi; Ranit Aharonov; Noam Slonim (ACL, 2020)

Active Learning for BERT: An Empirical Study. - Liat Ein-Dor; Alon Halfon; Ariel Gera; Eyal Shnarch; Lena Dankin; Leshem Choshen; Marina Danilevsky; Ranit Aharonov; Yoav Katz; Noam Slonim (EMNLP (1), 2020)

Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains. - Eyal Shnarch; Leshem Choshen; Guy Moshkowich; Ranit Aharonov; Noam Slonim (EMNLP (Findings), 2020)

A Survey of the State of Explainable AI for Natural Language Processing. - Marina Danilevsky; Kun Qian 002; Ranit Aharonov; Yannis Katsis; Ban Kawas; Prithviraj Sen (AACL/IJCNLP, 2020)

Improved Semantic Role Labeling using Parameterized Neighborhood Memory Adaptation. - Ishan Jindal; Ranit Aharonov; Siddhartha Brahma; Huaiyu Zhu 001; Yunyao Li 001 (CoRR, 2020)

YASO: A New Benchmark for Targeted Sentiment Analysis. - Matan Orbach; Orith Toledo-Ronen; Artem Spector; Ranit Aharonov; Yoav Katz; Noam Slonim (CoRR, 2020)

Overview of the 2021 Key Point Analysis Shared Task. - Roni Friedman; Lena Dankin; Yufang Hou 001; Ranit Aharonov; Yoav Katz; Noam Slonim (ArgMining@EMNLP, 2021)

TWEETSUMM - A Dialog Summarization Dataset for Customer Service. - Guy Feigenblat; R. Chulaka Gunasekara; Benjamin Sznajder; Sachindra Joshi; David Konopnicki; Ranit Aharonov (EMNLP (Findings), 2021)

Using Question Answering Rewards to Improve Abstractive Summarization. - R. Chulaka Gunasekara; Guy Feigenblat; Benjamin Sznajder; Ranit Aharonov; Sachindra Joshi (EMNLP (Findings), 2021)

YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews. - Matan Orbach; Orith Toledo-Ronen; Artem Spector; Ranit Aharonov; Yoav Katz; Noam Slonim (EMNLP (1), 2021)

An autonomous debating system. - Noam Slonim; Yonatan Bilu; Carlos Alzate; Roy Bar-Haim; Ben Bogin; Francesca Bonin; Leshem Choshen; Edo Cohen-Karlik; Lena Dankin; Lilach Edelstein; Liat Ein-Dor; Roni Friedman-Melamed; et al. (Nat., 2021)

Fortunately, Discourse Markers Can Enhance Language Models for Sentiment Analysis. - Liat Ein-Dor; Ilya Shnayderman; Artem Spector; Lena Dankin; Ranit Aharonov; Noam Slonim (AAAI, 2022)

Quality Controlled Paraphrase Generation. - Elron Bandel; Ranit Aharonov; Michal Shmueli-Scheuer; Ilya Shnayderman; Noam Slonim; Liat Ein-Dor (ACL (1), 2022)

Cluster & Tune: Boost Cold Start Performance in Text Classification. - Eyal Shnarch; Ariel Gera; Alon Halfon; Lena Dankin; Leshem Choshen; Ranit Aharonov; Noam Slonim (ACL (1), 2022)

Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours. - Eyal Shnarch; Alon Halfon; Ariel Gera; Marina Danilevsky; Yannis Katsis; Leshem Choshen; Martín Santillán Cooper; Dina Epelboim; Zheng Zhang 043; Dakuo Wang; Lucy Yip; Liat Ein-Dor; et al. (CoRR, 2022)