Evaluating models' local decision boundaries via contrast sets M Gardner, Y Artzi, V Basmova, J Berant, B Bogin, S Chen, P Dasigi, ... arXiv preprint arXiv:2004.02709, 2020 | 447 | 2020 |
Adversarial removal of demographic attributes from text data Y Elazar, Y Goldberg arXiv preprint arXiv:1808.06640, 2018 | 342 | 2018 |
Null it out: Guarding protected attributes by iterative nullspace projection S Ravfogel, Y Elazar, H Gonen, M Twiton, Y Goldberg arXiv preprint arXiv:2004.07667, 2020 | 321 | 2020 |
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 | 272 | 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 | 218 | 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 | 196 | 2021 |
Contrastive explanations for model interpretability A Jacovi, S Swayamdipta, S Ravfogel, Y Elazar, Y Choi, Y Goldberg arXiv preprint arXiv:2103.01378, 2021 | 92 | 2021 |
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 | 80* | 2023 |
Do language embeddings capture scales? X Zhang, D Ramachandran, I Tenney, Y Elazar, D Roth arXiv preprint arXiv:2010.05345, 2020 | 78 | 2020 |
How large are lions? inducing distributions over quantitative attributes Y Elazar, A Mahabal, D Ramachandran, T Bedrax-Weiss, D Roth arXiv preprint arXiv:1906.01327, 2019 | 56 | 2019 |
Few-shot fine-tuning vs. in-context learning: A fair comparison and evaluation M Mosbach, T Pimentel, S Ravfogel, D Klakow, Y Elazar arXiv preprint arXiv:2305.16938, 2023 | 53 | 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 | 53 | 2019 |
First align, then predict: Understanding the cross-lingual ability of multilingual BERT B Muller, Y Elazar, B Sagot, D Seddah arXiv preprint arXiv:2101.11109, 2021 | 48 | 2021 |
Back to square one: Artifact detection, training and commonsense disentanglement in the Winograd schema Y Elazar, H Zhang, Y Goldberg, D Roth arXiv preprint arXiv:2104.08161, 2021 | 47 | 2021 |
It's not Greek to mBERT: inducing word-level translations from multilingual BERT H Gonen, S Ravfogel, Y Elazar, Y Goldberg arXiv preprint arXiv:2010.08275, 2020 | 44 | 2020 |
Measuring causal effects of data statistics on language model'sfactual'predictions Y Elazar, N Kassner, S Ravfogel, A Feder, A Ravichander, M Mosbach, ... arXiv preprint arXiv:2207.14251, 2022 | 37 | 2022 |
Olmo: Accelerating the science of language models D Groeneveld, I Beltagy, P Walsh, A Bhagia, R Kinney, O Tafjord, AH Jha, ... arXiv preprint arXiv:2402.00838, 2024 | 32 | 2024 |
Privacy and fairness in recommender systems via adversarial training of user representations YS Resheff, Y Elazar, M Shahar, OS Shalom arXiv preprint arXiv:1807.03521, 2018 | 27 | 2018 |
Revisiting few-shot relation classification: Evaluation data and classification schemes O Sabo, Y Elazar, Y Goldberg, I Dagan Transactions of the Association for Computational Linguistics 9, 691-706, 2021 | 26 | 2021 |
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, ... arXiv preprint arXiv:2402.00159, 2024 | 24 | 2024 |