Papers by Elena Volodina

5 papers
Superlim: A Swedish Language Understanding Evaluation Benchmark (2023.emnlp-main)

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Challenge: In this paper, we present a multi-task benchmark for Swedish language models . we address methodological challenges, such as mitigating the Anglocentric bias when creating datasets for a less-resourced language .
Approach: They propose a multi-task NLP benchmark for Swedish language models . they propose to use superlim to evaluate Swedish language model performance .
Outcome: The proposed benchmark does not approach ceiling performance on any of the tasks, suggesting it is difficult to implement.
Towards Privacy by Design in Learner Corpora Research: A Case of On-the-fly Pseudonymization of Swedish Learner Essays (2020.coling-main)

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Challenge: An ongoing project aims at automating pseudonymization of learner essays . 89% of the personal information can be successfully identified in learner data .
Approach: They propose to use rule-based methods to detect 15 categories out of 19 suggested by the authors.
Outcome: The proposed methods detect 15 categories out of 19 suggested by the authors . 89% of the personal information can be successfully identified in learner data and annotated correctly with an inter-annotator agreement of 86% measured as Fleiss kappa and Krippendorff’s alpha.
Pseudonymization Categories across Domain Boundaries (2024.lrec-main)

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Challenge: Linguistic data can contain personal information, which is limited in accessibility . a universal system of tags for categorizing PIIs could be developed to replace them .
Approach: They analyze tagsets used for anonymization and pseudonymization to find out what kinds of PII appear in different domains.
Outcome: The proposed system would allow for dynamic pseudonymization while keeping the data readable and useful for future research.
Towards an Ideal Tool for Learner Error Annotation (2024.lrec-main)

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Challenge: 'correction annotation' is a technique that has been used for many years to correct errors in learner corpora.
Approach: They propose to use SVALA to annotate and analyse corrections in learner corpora using a parallel aligned approach to visualisation and annotation.
Outcome: The proposed tool supports multiple annotation systems, localisation into other languages, and the development of more complex annotation systems.
UniversalCEFR: Enabling Open Multilingual Research on Language Proficiency Assessment (2025.emnlp-main)

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Challenge: Language proficiency research plays a central role in education and often intersects with advances in linguistics and AI.
Approach: They propose a multilingual multidimensional dataset of texts annotated according to the CEFR scale in 13 languages.
Outcome: The proposed dataset supports linguistic features and pretrained models in multilingual CEFR level assessment.

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