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Can Transformers Process Recursive Nested Constructions, Like Humans?

, , , and . COLING, page 3226-3232. International Committee on Computational Linguistics, (2022)

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Probabilistic Graphical Models of Dyslexia., , , and . KDD, page 1919-1928. ACM, (2015)Metric Learning for Phoneme Perception., , , , and . CoRR, (2018)Can Transformers Process Recursive Nested Constructions, Like Humans?, , , and . COLING, page 3226-3232. International Committee on Computational Linguistics, (2022)Language acquisition: do children and language models follow similar learning stages?, , and . ACL (Findings), page 12205-12218. Association for Computational Linguistics, (2023)Causal Transformers Perform Below Chance on Recursive Nested Constructions, Unlike Humans., , , and . CoRR, (2021)Information-Restricted Neural Language Models Reveal Different Brain Regions' Sensitivity to Semantics, Syntax and Context., , , and . CoRR, (2023)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models, , , , , , , , , and 441 other author(s). (2022)cite arxiv:2206.04615Comment: 27 pages, 17 figures + references and appendices, repo: https://github.com/google/BIG-bench.Single-cell activity in human STG during perception of phonemes is organized according to manner of articulation., , , , and . NeuroImage, (2021)Can RNNs learn Recursive Nested Subject-Verb Agreements?, , , , , and . CoRR, (2021)Distinguishing between Different Syntactic Roles of Identical Words in Normal Reading: an ERP Study., , , and . EAPCogSci, volume 1419 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)