| Evaluating models' local decision boundaries via contrast sets M Gardner, Y Artzi, V Basmova, J Berant, B Bogin, S Chen, P Dasigi, ... Findings of EMNLP 2020, 2020 | 481 | 2020 |
| Null it out: Guarding protected attributes by iterative nullspace projection S Ravfogel, Y Elazar, H Gonen, M Twiton, Y Goldberg ACL 2020, 2020 | 402 | 2020 |
| Adversarial removal of demographic attributes from text data Y Elazar, Y Goldberg EMNLP 2018, 2018 | 377 | 2018 |
| Measuring and improving consistency in pretrained language models Y Elazar, N Kassner, S Ravfogel, A Ravichander, E Hovy, H Schütze, ... Transactions of the Association for Computational Linguistics 9, 1012-1031, 2021 | 343 | 2021 |
| oLMpics-on what language model pre-training captures A Talmor, Y Elazar, Y Goldberg, J Berant Transactions of the Association for Computational Linguistics 8, 743-758, 2020 | 245 | 2020 |
| Amnesic probing: Behavioral explanation with amnesic counterfactuals Y Elazar, S Ravfogel, A Jacovi, Y Goldberg Transactions of the Association for Computational Linguistics 9, 160-175, 2021 | 240* | 2021 |
| Olmo: Accelerating the science of language models D Groeneveld, I Beltagy, P Walsh, A Bhagia, R Kinney, O Tafjord, AH Jha, ... 🏆 Best Paper Award 🏆 ACL 2024, 2024 | 180* | 2024 |
| Dolma: An open corpus of three trillion tokens for language model pretraining research L Soldaini, R Kinney, A Bhagia, D Schwenk, D Atkinson, R Authur, ... 🏆 Best Paper Award 🏆 ACL 2024, 2024 | 136* | 2024 |
| A taxonomy and review of generalization research in NLP D Hupkes, M Giulianelli, V Dankers, M Artetxe, Y Elazar, T Pimentel, ... Nature Machine Intelligence 5 (10), 1161-1174, 2023 | 113* | 2023 |
| Contrastive explanations for model interpretability A Jacovi, S Swayamdipta, S Ravfogel, Y Elazar, Y Choi, Y Goldberg EMNLP 2021, 2021 | 107 | 2021 |
| Few-shot fine-tuning vs. in-context learning: A fair comparison and evaluation M Mosbach, T Pimentel, S Ravfogel, D Klakow, Y Elazar Findings of ACL 2023, 2023 | 93 | 2023 |
| Do language embeddings capture scales? X Zhang, D Ramachandran, I Tenney, Y Elazar, D Roth Findings of EMNLP 2020, 2020 | 86 | 2020 |
| A survey on data selection for language models A Albalak, Y Elazar, SM Xie, S Longpre, N Lambert, X Wang, ... TMLR 2024, 2024 | 68 | 2024 |
| How large are lions? inducing distributions over quantitative attributes Y Elazar, A Mahabal, D Ramachandran, T Bedrax-Weiss, D Roth ACL 2019, 2019 | 68 | 2019 |
| What's In My Big Data? Y Elazar, A Bhagia, I Magnusson, A Ravichander, D Schwenk, A Suhr, ... ICLR 2024, spotlight, 2023 | 67 | 2023 |
| Adversarial removal of demographic attributes revisited M Barrett, Y Kementchedjhieva, Y Elazar, D Elliott, A Søgaard Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 58 | 2019 |
| First align, then predict: Understanding the cross-lingual ability of multilingual BERT B Muller, Y Elazar, B Sagot, D Seddah EACL 2021, 2021 | 56 | 2021 |
| It's not Greek to mBERT: inducing word-level translations from multilingual BERT H Gonen, S Ravfogel, Y Elazar, Y Goldberg BlackboxNLP 2020, 2020 | 54 | 2020 |
| Back to square one: Artifact detection, training and commonsense disentanglement in the winograd schema Y Elazar, H Zhang, Y Goldberg, D Roth EMNLP 2021, 2021 | 52 | 2021 |
| Measuring causal effects of data statistics on language model's 'factual' predictions Y Elazar, N Kassner, S Ravfogel, A Feder, A Ravichander, M Mosbach, ... arXiv preprint arXiv:2207.14251, 2022 | 48 | 2022 |
Yoav GoldbergProfessor, Bar Ilan University. Research Director, AI2-IsraelVerified email at cs.biu.ac.il
