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Structural probing work has found evidence for latent syntactic information in pre-trained language models.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
Earlier work this paper cites.
Assessing BERT’s syntactic abilities
Yoav Goldberg. 2019 · 1901
Earlier work this paper cites.
RoBERTa: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Wietse de Vries, Andreas van Cranenburgh, Arianna Bisazza, Tommaso Caselli, Gertjan van Noord, and Malvina Nissim. 2019 · 1912
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Direct and indirect effects
Judea Pearl. 2001 · 2001
Earlier work this paper cites.
Semantics of causal DAG models and the identification of direct and indirect effects
James M. Robins. 2003 · 2003
Earlier work this paper cites.
Assessing the ability of LSTMs to learn syntax-sensitive dependencies
Tal Linzen, Emmanuel Dupoux, and Yoav Goldberg. 2016 · 2016
Earlier work this paper cites.
Targeted syntactic evaluation of language models
Rebecca Marvin and Tal Linzen. 2018 · 2018
Earlier work this paper cites.
Transformer-XL: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc Le, and Ruslan Salakhutdinov. 2019 · 2019
Earlier work this paper cites.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
Designing and interpreting probes with control tasks
John Hewitt and Percy Liang. 2019 · 2019
Earlier work this paper cites.
A structural probe for finding syntax in word representations
John Hewitt and Christopher D. Manning. 2019 · 2019
Earlier work this paper cites.
The emergence of number and syntax units in LSTM language models
Yair Lakretz, German Kruszewski, Theo Desbordes, Dieuwke Hupkes, Stanislas Dehaene, and Marco Baroni. 2019 · 2019
Earlier work this paper cites.
Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
Tom McCoy, Ellie Pavlick, and Tal Linzen. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Studying the inductive biases of RNNs with synthetic variations of natural languages
Shauli Ravfogel, Yoav Goldberg, and Tal Linzen. 2019 · 2019
Cited alongside, same era.
Multilingual is not enough: BERT for Finnish
Antti Virtanen, Jenna Kanerva, Rami Ilo, Jouni Luoma, Juhani Luotolahti, Tapio Salakoski, Filip Ginter, and Sampo Pyysalo. 2019 · 2019
Cited alongside, same era.
Beto, Bentz, Becas: The surprising cross-lingual effectiveness of BERT
Shijie Wu and Mark Dredze. 2019 · 2019
Cited alongside, same era.
XLNet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. 2019 · 2019
Cited alongside, same era.
Finding universal grammatical relations in multilingual BERT
Learning which features matter: RoBERTa acquires a preference for linguistic generalizations (eventually)
Alex Warstadt, Yian Zhang, Xiaocheng Li, Haokun Liu, and Samuel R. Bowman. 2020 · 2020
Later among the works it cites.
Sparse interventions in language models with differentiable masking
Nicola De Cao, Leon Schmid, Dieuwke Hupkes, and Ivan Titov. 2021 · 2021
Later among the works it cites.
Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals
Yanai Elazar, Shauli Ravfogel, Alon Jacovi, and Yoav Goldberg. 2021 · 2021
Later among the works it cites.
Causal analysis of syntactic agreement mechanisms in neural language models
Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart Shieber, Tal Linzen, and Yonatan Belinkov. 2021 · 2021
Later among the works it cites.
Mechanisms for handling nested dependencies in neural-network language models and humans
Yair Lakretz, Dieuwke Hupkes, Alessandra Vergallito, Marco Marelli, Marco Baroni, and Stanislas Dehaene. 2021 · 2021
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Ethan A. Chi, John Hewitt, and Christopher D. Manning. 2020 · 2020
Cited alongside, same era.
Unsupervised cross-lingual representation learning at scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
Cited alongside, same era.
A systematic assessment of syntactic generalization in neural language models
Jennifer Hu, Jon Gauthier, Peng Qian, Ethan Wilcox, and Roger Levy. 2020 · 2020
Cited alongside, same era.
Emergent linguistic structure in artificial neural networks trained by self-supervision
Christopher D Manning, Kevin Clark, John Hewitt, Urvashi Khandelwal, and Omer Levy. 2020 · 2020
Cited alongside, same era.
CamemBERT: a tasty French language model
Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, Yoann Dupont, Laurent Romary, Éric de la Clergerie, Djamé Seddah, and Benoît Sagot. 2020 · 2020
Cited alongside, same era.
Cross-linguistic syntactic evaluation of word prediction models
Aaron Mueller, Garrett Nicolai, Panayiota Petrou-Zeniou, Natalia Talmina, and Tal Linzen. 2020 · 2020
Cited alongside, same era.
Null it out: Guarding protected attributes by iterative nullspace projection
Shauli Ravfogel, Yanai Elazar, Hila Gonen, Michael Twiton, and Yoav Goldberg. 2020 · 2020
Cited alongside, same era.
Later among the works it cites.
Few-shot learning with multilingual language models
Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, Tianlu Wang, Shuohui Chen, Daniel Simig, Myle Ott, Naman Goyal, Shruti Bhosale, Jingfei Du, Ramakanth Pasunuru, Sam Shleifer, Punit Singh Koura, Vishrav Chaudhary, Brian O’Horo, Jeff Wang, Luke Zettlemoyer, Zornitsa Kozareva, Mona T. Diab, Veselin Stoyanov, and Xian Li. 2021 · 2021
Later among the works it cites.
Counterfactual interventions reveal the causal effect of relative clause representations on agreement prediction
Shauli Ravfogel, Grusha Prasad, Tal Linzen, and Yoav Goldberg. 2021 · 2021
Later among the works it cites.
Exploiting cloze-questions for few-shot text classification and natural language inference
Timo Schick and Hinrich Schütze. 2021 · 2021
Later among the works it cites.
Masked language modeling and the distributional hypothesis: Order word matters pre-training for little
Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, and Douwe Kiela. 2021 · 2021
Later among the works it cites.
On the pitfalls of analyzing individual neurons in language models
Omer Antverg and Yonatan Belinkov. 2022 · 2022
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Locating and editing factual associations in GPT
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022 · 2022
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Coloring the blank slate: Pre-training imparts a hierarchical inductive bias to sequence-to-sequence models
Aaron Mueller, Robert Frank, Tal Linzen, Luheng Wang, and Sebastian Schuster. 2022 · 2022
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Same neurons, different languages: Probing morphosyntax in multilingual pre-trained models
Karolina Stanczak, Edoardo Ponti, Lucas Torroba Hennigen, Ryan Cotterell, and Isabelle Augenstein. 2022 · 2022
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When does syntax mediate neural language model performance? evidence from dropout probes
Mycal Tucker, Tiwalayo Eisape, Peng Qian, Roger Levy, and Julie Shah. 2022 · 2022
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