The Sensitivity of Annotator Bias to Task Definitions in Argument Mining

1 code implementation • LREC (LAW) 2022 • Terne Sasha Thorn Jakobsen, Maria Barrett, Anders Søgaard, David Lassen

NLP models are dependent on the data they are trained on, including how this data is annotated.

Argument Mining

Being Right for Whose Right Reasons?

no code implementations • 1 Jun 2023 • Terne Sasha Thorn Jakobsen, Laura Cabello, Anders Søgaard

Explainability methods are used to benchmark the extent to which model predictions align with human rationales i. e., are 'right for the right reasons'.

Common Sense Reasoning Fairness +1

What Factors Should Paper-Reviewer Assignments Rely On? Community Perspectives on Issues and Ideals in Conference Peer-Review

1 code implementation • NAACL 2022 • Terne Sasha Thorn Jakobsen, Anna Rogers

Both scientific progress and individual researcher careers depend on the quality of peer review, which in turn depends on paper-reviewer matching.

Spurious Correlations in Cross-Topic Argument Mining

1 code implementation • Joint Conference on Lexical and Computational Semantics 2021 • Terne Sasha Thorn Jakobsen, Maria Barrett, Anders S{\o}gaard

Recent work in cross-topic argument mining attempts to learn models that generalise across topics rather than merely relying on within-topic spurious correlations.

Argument Mining Topic Models