Papers by Terne Sasha Thorn Jakobsen
Being Right for Whose Right Reasons? (2023.acl-long)
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| Challenge: | Existing work has failed to acknowledge that what counts as a rationale is subjective. |
| Approach: | They propose to use demographic annotations to augment existing datasets to ask what demographics our models align with and whose reasoning patterns they align with. |
| Outcome: | The proposed model rationales align better with older and/or white annotators, and are biased towards older and white anorators. |
Spurious Correlations in Cross-Topic Argument Mining (2021.starsem-1)
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| Challenge: | Recent work in cross-topic argument mining attempts to learn models that generalise across topics rather than relying on within-topic spurious correlations. |
| Approach: | They propose to use linear approximations of decision boundaries and manual feature grouping to learn models that generalise across topics rather than relying on within-topic spurious correlations. |
| Outcome: | The proposed model generalise across topics rather than relying on spurious correlations. |
Research Community Perspectives on “Intelligence” and Large Language Models (2025.findings-acl)
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| Challenge: | Despite the widespread use of ‘artificial intelligence’ (AI) framing in NLP research, it is not clear what researchers mean by ”intelligence”. |
| Approach: | They propose to use the term "AI" to describe the perception of a system as intelligent, but note that it is not accepted by the majority of respondents. |
| Outcome: | The results suggest that the perception of the current NLP systems as 'intelligent' is a minority position (29%). |