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%0 Conference Proceedings
%T Assessing the ability of Transformer-based Neural Models to represent structurally unbounded dependencies
%A Da Costa, Jillian
%A Chaves, Rui
%S Proceedings of the Society for Computation in Linguistics 2020
%D 2020
%8 jan
%I Association for Computational Linguistics
%C New York, New York
%F da-costa-chaves-2020-assessing
%U https://aclanthology.org/2020.scil-1.2
%P 12-21

Markdown (Informal)

[Assessing the ability of Transformer-based Neural Models to represent structurally unbounded dependencies](https://aclanthology.org/2020.scil-1.2) (Da Costa & Chaves, SCiL 2020)

• Assessing the ability of Transformer-based Neural Models to represent structurally unbounded dependencies (Da Costa & Chaves, SCiL 2020)

ACL

• Jillian Da Costa and Rui Chaves. 2020. Assessing the ability of Transformer-based Neural Models to represent structurally unbounded dependencies. In Proceedings of the Society for Computation in Linguistics 2020, pages 12–21, New York, New York. Association for Computational Linguistics.