| 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 | 960 | 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 | 737 | 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 | 130 | 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 | 121 | 2020 |
| 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 | 110 | 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, ... Proceedings of the Eighth Joint Conference on Lexical and Computational …, 2019 | 98 | 2019 |
| 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 | 81 | 2020 |
| 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 | 77 | 2018 |
| 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 | 50 | 2019 |
| RNNs Implicitly Implement Tensor Product Representations RT McCoy, T Linzen, E Dunbar, P Smolensky International Conference on Learning Representations, 2019 | 49 | 2019 |
| 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 | 44 | 2023 |
| 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 | 36 | 2022 |
| 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 | 33 | 2020 |
| 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 | 30 | 2017 |
| 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 |
| Phonologically informed edit distance algorithms for word alignment with low-resource languages RT McCoy, R Frank Proceedings of the Society for Computation in Linguistics (SCiL) 2018, 102-112, 2018 | 21 | 2018 |
| 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 | 20 | 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 | 20 | 2019 |
| 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 | 14 | 2020 |
| Representations of Syntax [MASK] Useful: Effects of Constituency and Dependency Structure in Recursive LSTMs MA Lepori, T Linzen, RT McCoy Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 12 | 2020 |
Tal LinzenNew York UniversityVerified email at nyu.edu
