| 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 | 256 | 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 | 249 | 2021 |
| 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 | 81 | 2020 |
| Zero-shot text classification with self-training A Gera, A Halfon, E Shnarch, Y Perlitz, L Ein-Dor, N Slonim arXiv preprint arXiv:2210.17541, 2022 | 61 | 2022 |
| 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 |
| Efficient benchmarking (of language models) Y Perlitz, E Bandel, A Gera, O Arviv, L Ein-Dor, E Shnarch, N Slonim, ... arXiv preprint arXiv:2308.11696, 2023 | 27 | 2023 |
| 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 | 27 | 2022 |
| Bumble bee workers give up sleep to care for offspring that are not their own M Nagari, A Gera, S Jonsson, G Bloch Current Biology 29 (20), 3488-3493. e4, 2019 | 27 | 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 |
| Argument invention from first principles Y Bilu, A Gera, D Hershcovich, B Sznajder, D Lahav, G Moshkowich, ... arXiv preprint arXiv:1908.08336, 2019 | 27 | 2019 |
| 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 |
| The benefits of bad advice: Autocontrastive decoding across model layers A Gera, R Friedman, O Arviv, C Gunasekara, B Sznajder, N Slonim, ... arXiv preprint arXiv:2305.01628, 2023 | 17 | 2023 |
| Active learning for natural language generation Y Perlitz, A Gera, M Shmueli-Scheuer, D Sheinwald, N Slonim, L Ein-Dor arXiv preprint arXiv:2305.15040, 2023 | 8 | 2023 |
| Do these LLM benchmarks agree? Fixing benchmark evaluation with BenchBench Y Perlitz, A Gera, O Arviv, A Yehudai, E Bandel, E Shnarch, ... arXiv preprint arXiv:2407.13696, 2024 | 6* | 2024 |
| Unitxt: Flexible, shareable and reusable data preparation and evaluation for generative ai E Bandel, Y Perlitz, E Venezian, R Friedman-Melamed, O Arviv, M Orbach, ... arXiv preprint arXiv:2401.14019, 2024 | 5 | 2024 |
| Controversy in context B Sznajder, A Gera, Y Bilu, D Sheinwald, E Rabinovich, R Aharonov, ... arXiv preprint arXiv:1908.07491, 2019 | 5 | 2019 |
| Label-efficient model selection for text generation SA Tahan, A Gera, B Sznajder, L Choshen, LE Dor, E Shnarch Proceedings of the 62nd Annual Meeting of the Association for Computational …, 2024 | 4* | 2024 |
| JuStRank: Benchmarking LLM Judges for System Ranking A Gera, O Boni, Y Perlitz, R Bar-Haim, L Eden, A Yehudai arXiv preprint arXiv:2412.09569, 2024 | 2 | 2024 |
| Cluster & tune: Enhance bert performance in low resource text classification E Shnarch, A Gera, A Halfon, L Dankin, L Choshen, R Aharonov, ... | 2 | 2021 |
| Signals from the brood modulate the sleep of brood tending bumblebee workers M Nagari, A Gera, S Jonsson, G Bloch BioRxiv, 500744, 2018 | 2 | 2018 |
Noam SlonimDistinguished Engineer at IBM ResearchVerified email at il.ibm.com
