Show me your evidence-an automatic method for context dependent evidence detection R Rinott, L Dankin, C Alzate, MM Khapra, E Aharoni, N Slonim Proceedings of the 2015 conference on empirical methods in natural language …, 2015 | 298 | 2015 |
Active learning for BERT: an empirical study LE Dor, A Halfon, A Gera, E Shnarch, L Dankin, L Choshen, M Danilevsky, ... Proceedings of the 2020 conference on empirical methods in natural language …, 2020 | 244 | 2020 |
An autonomous debating system N Slonim, Y Bilu, C Alzate, R Bar-Haim, B Bogin, F Bonin, L Choshen, ... Nature 591 (7850), 379-384, 2021 | 241 | 2021 |
Are you convinced? choosing the more convincing evidence with a Siamese network M Gleize, E Shnarch, L Choshen, L Dankin, G Moshkowich, R Aharonov, ... arXiv preprint arXiv:1907.08971, 2019 | 88 | 2019 |
Will it blend? blending weak and strong labeled data in a neural network for argumentation mining E Shnarch, C Alzate, L Dankin, M Gleize, Y Hou, L Choshen, R Aharonov, ... Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 84 | 2018 |
Corpus wide argument mining—a working solution L Ein-Dor, E Shnarch, L Dankin, A Halfon, B Sznajder, A Gera, C Alzate, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7683-7691, 2020 | 80 | 2020 |
Financial event extraction using Wikipedia-based weak supervision L Ein-Dor, A Gera, O Toledo-Ronen, A Halfon, B Sznajder, L Dankin, ... arXiv preprint arXiv:1911.10783, 2019 | 30 | 2019 |
A dataset of general-purpose rebuttal M Orbach, Y Bilu, A Gera, Y Kantor, L Dankin, T Lavee, L Kotlerman, ... arXiv preprint arXiv:1909.00393, 2019 | 27 | 2019 |
Cluster & tune: Boost cold start performance in text classification E Shnarch, A Gera, A Halfon, L Dankin, L Choshen, R Aharonov, ... arXiv preprint arXiv:2203.10581, 2022 | 26 | 2022 |
Overview of the 2021 key point analysis shared task R Friedman-Melamed, L Dankin, Y Hou, R Aharonov, Y Katz, N Slonim Conference on Empirical Methods in Natural Language Processing, 2021 | 23* | 2021 |
Label sleuth: From unlabeled text to a classifier in a few hours E Shnarch, A Halfon, A Gera, M Danilevsky, Y Katsis, L Choshen, ... arXiv preprint arXiv:2208.01483, 2022 | 21 | 2022 |
Towards effective rebuttal: Listening comprehension using corpus-wide claim mining T Lavee, M Orbach, L Kotlerman, Y Kantor, S Gretz, L Dankin, S Mirkin, ... arXiv preprint arXiv:1907.11889, 2019 | 19 | 2019 |
Claims on demand–an initial demonstration of a system for automatic detection and polarity identification of context dependent claims in massive corpora N Slonim, E Aharoni, C Alzate, R Bar-Haim, Y Bilu, L Dankin, I Eiron, ... Proceedings of COLING 2014, the 25th International Conference on …, 2014 | 12 | 2014 |
Fortunately, discourse markers can enhance language models for sentiment analysis L Ein-Dor, I Shnayderman, A Spector, L Dankin, R Aharonov, N Slonim Proceedings of the AAAI Conference on Artificial Intelligence 36 (10), 10608 …, 2022 | 6 | 2022 |
A hackathon for classical Tibetan O Almogi, L Dankin, N Dershowitz, L Wolf Journal of Data Mining & Digital Humanities, 2019 | 6 | 2019 |
Zero-shot Topical Text Classification with LLMs-an Experimental Study S Gretz, A Halfon, I Shnayderman, O Toledo-Ronen, A Spector, L Dankin, ... Findings of the Association for Computational Linguistics: EMNLP 2023, 9647-9676, 2023 | 4 | 2023 |
Automatic metaphor interpretation using word embeddings K Bar, N Dershowitz, L Dankin arXiv preprint arXiv:2010.02665, 2020 | 4 | 2020 |
Context-dependent evidence detection E Aharoni, L Dankin, D Gutfreund, T Lavee, R Levy, R Rinott, N Slonim US Patent 10,013,482, 2018 | 4 | 2018 |
Stemming and segmentation for Classical Tibetan O Almogi, L Dankin, N Dershowitz, Y Hoffman, D Pauls, D Wangchuk, ... Computational Linguistics and Intelligent Text Processing: 17th …, 2018 | 4 | 2018 |
Can Yes-No Question-Answering Models be Useful for Few-Shot Metaphor Detection? L Dankin, K Bar, N Dershowitz Proceedings of the 3rd Workshop on Figurative Language Processing (FLP), 125-130, 2022 | 3 | 2022 |