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The Language Model Understood the Prompt was Ambiguous: Probing Syntactic Uncertainty Through Generation


Sep 16, 2021
Laura Aina, Tal Linzen

* To appear in Proceedings of BlackboxNLP 2021: Analyzing and Interpreting Neural Networks for NLP 

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Frequency Effects on Syntactic Rule Learning in Transformers


Sep 14, 2021
Jason Wei, Dan Garrette, Tal Linzen, Ellie Pavlick

* Camera ready for EMNLP 2021 

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NOPE: A Corpus of Naturally-Occurring Presuppositions in English


Sep 14, 2021
Alicia Parrish, Sebastian Schuster, Alex Warstadt, Omar Agha, Soo-Hwan Lee, Zhuoye Zhao, Samuel R. Bowman, Tal Linzen

* CoNLL 2021. Data and code available at https://github.com/nyu-mll/nope 

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The MultiBERTs: BERT Reproductions for Robustness Analysis


Jun 30, 2021
Thibault Sellam, Steve Yadlowsky, Jason Wei, Naomi Saphra, Alexander D'Amour, Tal Linzen, Jasmijn Bastings, Iulia Turc, Jacob Eisenstein, Dipanjan Das, Ian Tenney, Ellie Pavlick

* Checkpoints and example analyses: http://goo.gle/multiberts 

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Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models


Jun 22, 2021
Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart Shieber, Tal Linzen, Yonatan Belinkov

* Accepted to ACL-IJCNLP 2021 

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Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction


May 19, 2021
Shauli Ravfogel, Grusha Prasad, Tal Linzen, Yoav Goldberg

* Equal contribution by SR and GP. Uploaded new version to fix typo in the abstract 

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Evaluating Groundedness in Dialogue Systems: The BEGIN Benchmark


Apr 30, 2021
Nouha Dziri, Hannah Rashkin, Tal Linzen, David Reitter

* 12 pages, 2 figures 

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Does Putting a Linguist in the Loop Improve NLU Data Collection?


Apr 15, 2021
Alicia Parrish, William Huang, Omar Agha, Soo-Hwan Lee, Nikita Nangia, Alex Warstadt, Karmanya Aggarwal, Emily Allaway, Tal Linzen, Samuel R. Bowman

* 14 pages, 10 figures 

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COGS: A Compositional Generalization Challenge Based on Semantic Interpretation


Oct 12, 2020
Najoung Kim, Tal Linzen

* Accepted to EMNLP 2020 

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Universal linguistic inductive biases via meta-learning


Jun 29, 2020
R. Thomas McCoy, Erin Grant, Paul Smolensky, Thomas L. Griffiths, Tal Linzen

* To appear in the Proceedings of the 42nd Annual Conference of the Cognitive Science Society 

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Cross-Linguistic Syntactic Evaluation of Word Prediction Models


May 21, 2020
Aaron Mueller, Garrett Nicolai, Panayiota Petrou-Zeniou, Natalia Talmina, Tal Linzen

* Accepted for presentation at ACL 2020 

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How Can We Accelerate Progress Towards Human-like Linguistic Generalization?


May 03, 2020
Tal Linzen

* ACL 2020 

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Representations of Syntax [MASK] Useful: Effects of Constituency and Dependency Structure in Recursive LSTMs


Apr 30, 2020
Michael A. Lepori, Tal Linzen, R. Thomas McCoy

* To appear in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL-2020) 

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Syntactic Data Augmentation Increases Robustness to Inference Heuristics


Apr 24, 2020
Junghyun Min, R. Thomas McCoy, Dipanjan Das, Emily Pitler, Tal Linzen

* ACL 2020 

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Syntactic Structure from Deep Learning


Apr 22, 2020
Tal Linzen, Marco Baroni

* In press at Annual Reviews of Linguistics 

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Does syntax need to grow on trees? Sources of hierarchical inductive bias in sequence-to-sequence networks


Jan 10, 2020
R. Thomas McCoy, Robert Frank, Tal Linzen

* 12 pages, 10 figures; accepted to TACL 

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Discovering the Compositional Structure of Vector Representations with Role Learning Networks


Nov 17, 2019
Paul Soulos, Tom McCoy, Tal Linzen, Paul Smolensky


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BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performance


Nov 07, 2019
R. Thomas McCoy, Junghyun Min, Tal Linzen

* 7 pages, 4 figures 

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Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Models


Sep 23, 2019
Grusha Prasad, Marten van Schijndel, Tal Linzen

* CoNLL 2019 
* 9 pages paper, 2 pages references and 3 pages supplementary materials. Code for the templates and analyses can be found here: https://github.com/grushaprasad/RNN-Priming 

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Quantity doesn't buy quality syntax with neural language models


Aug 31, 2019
Marten van Schijndel, Aaron Mueller, Tal Linzen

* Accepted for presentation at EMNLP-IJCNLP 2019 

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Probing What Different NLP Tasks Teach Machines about Function Word Comprehension


Apr 25, 2019
Najoung Kim, Roma Patel, Adam Poliak, Alex Wang, Patrick Xia, R. Thomas McCoy, Ian Tenney, Alexis Ross, Tal Linzen, Benjamin Van Durme, Samuel R. Bowman, Ellie Pavlick

* Accepted to *SEM 2019 

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Analyzing and Interpreting Neural Networks for NLP: A Report on the First BlackboxNLP Workshop


Apr 05, 2019
Afra Alishahi, Grzegorz Chrupała, Tal Linzen


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Studying the Inductive Biases of RNNs with Synthetic Variations of Natural Languages


Mar 26, 2019
Shauli Ravfogel, Yoav Goldberg, Tal Linzen

* Accepted as a long paper in NAACL 2019 

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Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference


Feb 04, 2019
R. Thomas McCoy, Ellie Pavlick, Tal Linzen

* 8 pages plus references and appendices 

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Human few-shot learning of compositional instructions


Jan 14, 2019
Brenden M. Lake, Tal Linzen, Marco Baroni


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RNNs Implicitly Implement Tensor Product Representations


Dec 20, 2018
R. Thomas McCoy, Tal Linzen, Ewan Dunbar, Paul Smolensky

* 8 pages plus references and appendices 

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