| BLOOM: A 176B-Parameter Open-Access Multilingual Language Model TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... arXiv preprint arXiv:2211.05100, 2022 | 1772 | 2022 |
| What do you learn from context? Probing for sentence structure in contextualized word representations I Tenney, P Xia, B Chen, A Wang, A Poliak, RT McCoy, N Kim, ... | 988 | 2018 |
| COGS: A Compositional Generalization Challenge Based on Semantic Interpretation N Kim, T Linzen arXiv preprint arXiv:2010.05465, 2020 | 296 | 2020 |
| Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks Z Wu, L Qiu, A Ross, E Akyürek, B Chen, B Wang, N Kim, J Andreas, ... arXiv preprint arXiv:2307.02477, 2023 | 178 | 2023 |
| Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling A Wang, J Hula, P Xia, R Pappagari, RT McCoy, R Patel, N Kim, I Tenney, ... Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 124 | 2019 |
| Probing What Different NLP Tasks Teach Machines about Function Word Comprehension N Kim, R Patel, A Poliak, A Wang, P Xia, RT McCoy, I Tenney, A Ross, ... arXiv preprint arXiv:1904.11544, 2019 | 114 | 2019 |
| Inverse Scaling: When Bigger Isn't Better IR McKenzie, A Lyzhov, M Pieler, A Parrish, A Mueller, A Prabhu, ... arXiv preprint arXiv:2306.09479, 2023 | 92 | 2023 |
| LAMBADA: Backward Chaining for Automated Reasoning in Natural Language SM Kazemi, N Kim, D Bhatia, X Xu, D Ramachandran arXiv preprint arXiv:2212.13894, 2022 | 80 | 2022 |
| Testing the general deductive reasoning capacity of large language models using ood examples A Saparov, RY Pang, V Padmakumar, N Joshi, M Kazemi, N Kim, H He Advances in Neural Information Processing Systems 36, 2024 | 64 | 2024 |
| jiant 1.1: A software toolkit for research on general-purpose text understanding models A Wang, IF Tenney, Y Pruksachatkun, K Yu, J Hula, P Xia, R Pappagari, ... | 55 | 2019 |
| Implicit Discourse Relation Classification: We Need to Talk about Evaluation N Kim, S Feng, C Gunasekara, L Lastras Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 53 | 2020 |
| Inverse scaling can become u-shaped J Wei, N Kim, Y Tay, QV Le arXiv preprint arXiv:2211.02011, 2022 | 45 | 2022 |
| Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering N Kim, E Pavlick, BK Ayan, D Ramachandran arXiv preprint arXiv:2101.00391, 2021 | 39 | 2021 |
| Automatic scoring of semantic fluency N Kim, JH Kim, MK Wolters, SE MacPherson, JC Park Frontiers in Psychology 10, 1020, 2019 | 36 | 2019 |
| Entity Tracking in Language Models N Kim, S Schuster arXiv preprint arXiv:2305.02363, 2023 | 33 | 2023 |
| Uncontrolled Lexical Exposure Leads to Overestimation of Compositional Generalization in Pretrained Models N Kim, T Linzen, P Smolensky arXiv preprint arXiv:2212.10769, 2022 | 33 | 2022 |
| Boardgameqa: A dataset for natural language reasoning with contradictory information M Kazemi, Q Yuan, D Bhatia, N Kim, X Xu, V Imbrasaite, ... Advances in Neural Information Processing Systems 36, 2024 | 31 | 2024 |
| Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling SR Bowman, E Pavlick, E Grave, B Van Durme, A Wang, J Hula, P Xia, ... arXiv preprint arXiv:1812.10860, 2018 | 28 | 2018 |
| Personas as a Way to Model Truthfulness in Language Models N Joshi, J Rando, A Saparov, N Kim, H He arXiv preprint arXiv:2310.18168, 2023 | 26 | 2023 |
| Testing for Grammatical Category Abstraction in Neural Language Models N Kim, P Smolensky Proceedings of the Society for Computation in Linguistics 4 (1), 467-470, 2021 | 26 | 2021 |
Ellie PavlickBrown UniversityPotvrđena adresa e-pošte na brown.edu