| Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference RT McCoy, E Pavlick, T Linzen Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 1291 | 2019 |
| 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, ... International Conference on Learning Representations, 2019 | 955 | 2019 |
| Syntactic data augmentation increases robustness to inference heuristics J Min, RT McCoy, D Das, E Pitler, T Linzen Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 186 | 2020 |
| BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performance RT McCoy, J Min, T Linzen Proceedings of the 3rd BlackboxNLP Workshop on Analyzing and Interpreting …, 2020 | 172 | 2020 |
| How much do language models copy from their training data? evaluating linguistic novelty in text generation using raven RT McCoy, P Smolensky, T Linzen, J Gao, A Celikyilmaz Transactions of the Association for Computational Linguistics 11, 652-670, 2023 | 124 | 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 |
| Embers of autoregression show how large language models are shaped by the problem they are trained to solve RT McCoy, S Yao, D Friedman, MD Hardy, TL Griffiths Proceedings of the National Academy of Sciences 121 (41), e2322420121, 2024 | 123* | 2024 |
| Does syntax need to grow on trees? sources of hierarchical inductive bias in sequence-to-sequence networks RT McCoy, R Frank, T Linzen Transactions of the Association for Computational Linguistics 8, 125-140, 2020 | 123 | 2020 |
| 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, ... Proceedings of the Eighth Joint Conference on Lexical and Computational …, 2019 | 106 | 2019 |
| Revisiting the poverty of the stimulus: hierarchical generalization without a hierarchical bias in recurrent neural networks RT McCoy, R Frank, T Linzen Proceedings of the 40th Annual Conference of the Cognitive Science Society …, 2018 | 100 | 2018 |
| Neurocompositional computing: From the central paradox of cognition to a new generation of ai systems P Smolensky, R McCoy, R Fernandez, M Goldrick, J Gao AI Magazine 43 (3), 308-322, 2022 | 80 | 2022 |
| RNNs Implicitly Implement Tensor Product Representations RT McCoy, T Linzen, E Dunbar, P Smolensky International Conference on Learning Representations, 2019 | 66 | 2019 |
| jiant 1.2: 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, ... Note: http://jiant. info/Cited by: footnote 4, 2019 | 54 | 2019 |
| Discovering the compositional structure of vector representations with role learning networks P Soulos, T McCoy, T Linzen, P Smolensky Proceedings of the 3rd BlackboxNLP Workshop on Analyzing and Interpreting …, 2020 | 47 | 2020 |
| How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech A Yedetore, T Linzen, R Frank, RT McCoy arXiv preprint arXiv:2301.11462, 2023 | 35 | 2023 |
| TAG parsing with neural networks and vector representations of supertags. J Kasai, B Frank, T McCoy, O Rambow, A Nasr Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 32 | 2017 |
| Universal linguistic inductive biases via meta-learning RT McCoy, E Grant, P Smolensky, TL Griffiths, T Linzen Proceedings of the 42nd Annual Conference of the Cognitive Science Society …, 2020 | 31 | 2020 |
| Non-entailed subsequences as a challenge for natural language inference RT McCoy, T Linzen Proceedings of the Society for Computation in Linguistics 2 (1), 358-360, 2019 | 26 | 2019 |
| 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, ... | 25 | 2018 |
| Picking BERT's Brain: Probing for Linguistic Dependencies in Contextualized Embeddings Using Representational Similarity Analysis MA Lepori, RT McCoy Proceedings of the 28th International Conference on Computational …, 2020 | 24 | 2020 |
Tal LinzenNew York UniversityVerified email at nyu.edu
