limited-data

2 Papers Accepted to ACL 2021

2 papers by CopeNLU authors are accepted to appear at ACL 2021. One paper is on interpretability, examining how sparsity affects our ability to use attention as an explainability tool; whereas the other one is on scientific document understanding, introducing a new dataset for the task of cite-worthiness detection in scientific articles. Is Sparse Attention more Interpretable? Clara Meister, Stefan Lazov, Isabelle Augenstein, Ryan Cotterell. CiteWorth: Cite-Worthiness Detection for Improved Scientific Document Understanding.

Paper Accepted to EACL 2021

A paper by CopeNLU author is accepted to appear at EACL 2021. The paper aims to bridge the gap between high- and low-resource languages by investigating to what degree cross-lingual models share structural information about languages. Does Typological Blinding Impede Cross-Lingual Sharing?. Johannes Bjerva, Isabelle Augenstein.

Learning with Limited Labelled Data

Learning with limited labelled data, including multi-task learning, weakly supervised and zero-shot learning