| A survey on data selection for language models A Albalak, Y Elazar, SM Xie, S Longpre, N Lambert, X Wang, ... arXiv preprint arXiv:2402.16827, 2024 | 24 | 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 | 89* | 2023 |
| Adversarial removal of demographic attributes from text data Y Elazar, Y Goldberg arXiv preprint arXiv:1808.06640, 2018 | 348 | 2018 |
| 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 | 55 | 2019 |
| Adversarial user representations in recommender machine learning models YS Resheff, S Shahar, OS Shalom, Y Elazar US Patent 11,494,701, 2022 | 2 | 2022 |
| 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 | 201 | 2021 |
| Applying Intrinsic Debiasing on Downstream Tasks: Challenges and Considerations for Machine Translation B Iluz, Y Elazar, A Yehudai, G Stanovsky arXiv preprint arXiv:2406.00787, 2024 | | 2024 |
| At your fingertips: Extracting piano fingering instructions from videos A Moryossef, Y Elazar, Y Goldberg arXiv preprint arXiv:2303.03745, 2023 | 6* | 2023 |
| 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 | 46 | 2021 |
| Backtracking Mathematical Reasoning of Language Models to the Pretraining Data Y Razeghi, H Ivison, S Singh, Y Elazar The Second Tiny Papers Track at ICLR 2024, 0 | | |
| Calibrating large language models with sample consistency Q Lyu, K Shridhar, C Malaviya, L Zhang, Y Elazar, N Tandon, ... arXiv preprint arXiv:2402.13904, 2024 | 3 | 2024 |
| CIKQA: Learning commonsense inference with a unified knowledge-in-the-loop QA paradigm H Zhang, Y Huo, Y Elazar, Y Song, Y Goldberg, D Roth arXiv preprint arXiv:2210.06246, 2022 | 1 | 2022 |
| Contrastive explanations for model interpretability A Jacovi, S Swayamdipta, S Ravfogel, Y Elazar, Y Choi, Y Goldberg arXiv preprint arXiv:2103.01378, 2021 | 96 | 2021 |
| Detection and measurement of syntactic templates in generated text C Shaib, Y Elazar, JJ Li, BC Wallace arXiv preprint arXiv:2407.00211, 2024 | 2 | 2024 |
| Do language embeddings capture scales? X Zhang, D Ramachandran, I Tenney, Y Elazar, D Roth arXiv preprint arXiv:2010.05345, 2020 | 79 | 2020 |
| 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 | 38 | 2024 |
| Estimating the Causal Effect of Early ArXiving on Paper Acceptance Y Elazar, J Zhang, D Wadden, B Zhang, NA Smith Causal Learning and Reasoning, 913-933, 2024 | 2 | 2024 |
| Evaluating -Gram Novelty of Language Models Using Rusty-DAWG W Merrill, NA Smith, Y Elazar arXiv preprint arXiv:2406.13069, 2024 | 1 | 2024 |
| 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 | 454 | 2020 |
| 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 | 56 | 2023 |
Yoav GoldbergProfessor, Bar Ilan University. Research Director, AI2-Israel在 cs.biu.ac.il 的电子邮件经过验证
