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Tal Linzen
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Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
13762022
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
13302019
Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies
T Linzen, E Dupoux, Y Goldberg
Transactions of the Association for Computational Linguistics 4, 521-535, 2016
10782016
Colorless green recurrent networks dream hierarchically
K Gulordava, P Bojanowski, E Grave, T Linzen, M Baroni
Proceedings of the 16th Annual Conference of the North American Chapter of …, 2018
6792018
Targeted Syntactic Evaluation of Language Models
R Marvin, T Linzen
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
5022018
COGS: A Compositional Generalization Challenge Based on Semantic Interpretation
N Kim, T Linzen
EMNLP, 2020
2982020
Syntactic Structure from Deep Learning
T Linzen, M Baroni
Annual Reviews of Linguistics, 2021
2672021
How Can We Accelerate Progress Towards Human-like Linguistic Generalization?
T Linzen
Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020
2122020
Issues in evaluating semantic spaces using word analogies
T Linzen
Proceedings of the First Workshop on Evaluating Vector Space Representations …, 2016
2052016
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
1922020
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 BlackboxNLP 2020, 2019
1772019
Findings of the BabyLM Challenge: Sample-efficient pretraining on developmentally plausible corpora
A Warstadt, A Mueller, L Choshen, E Wilcox, C Zhuang, J Ciro, ...
Proceedings of the BabyLM Challenge at the 27th Conference on Computational …, 2023
146*2023
Uncertainty and expectation in sentence processing: evidence from subcategorization distributions
T Linzen, TF Jaeger
Cognitive Science 40 (6), 1382-1411, 2016
1452016
Human few-shot learning of compositional instructions
BM Lake, T Linzen, M Baroni
Proceedings of the 41st Annual Conference of the Cognitive Science Society, 2019
1412019
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
1342023
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
1252020
In Spoken Word Recognition, the Future Predicts the Past
L Gwilliams, T Linzen, D Poeppel, A Marantz
Journal of Neuroscience 38 (35), 7585-7599, 2018
1242018
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
1142019
Quantity doesn't buy quality syntax with neural language models
M van Schijndel, A Mueller, T Linzen
EMNLP 2019, 2019
1022019
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
1002018
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