Papers with textual complexity

3 papers
The iRead4Skills Intelligent Complexity Analyzer (2025.emnlp-demos)

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Challenge: 20% of EU adult population exhibits low-literacy and numeracy skills (EA, 2021).
Approach: iRead4Skills Intelligent Complexity Analyzer integrates a range of NLP components to assess input texts along multiple levels of granularity and linguistic dimensions in Portuguese, Spanish, and French.
Outcome: The system assigns four tailored difficulty levels and introduces four diagnostic yardsticks—textual structure, lexicon, syntax, and semantics—offering users actionable feedback on specific dimensions of textual complexity.
Scaling up Discourse Quality Annotation for Political Science (2022.lrec-1)

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Challenge: Existing annotations on deliberative quality are time-consuming and suffer from class imbalance . ephd thesis: deliberation is not only the output of the decision making, but also the discussion that leads up to it.
Approach: They propose to use data augmentation techniques to improve deliberative quality predictions in a standard dataset.
Outcome: The proposed methods outperform classifiers based on linguistic features and argument quality annotations with or without data augmentation.
Mining the uncertainty patterns of humans and models in the annotation of moral foundations and human values (2025.acl-long)

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Challenge: disagreement in annotation (HLV) is considered a constitutive feature of subjective tasks.
Approach: They investigate the relationship between disagreement in annotation and model uncertainty . they use linguistic features to calibrate models to HLV and uncertainty to analyze their impact on uncertainty.
Outcome: The proposed model uncertainty is calibrated to human label variation (HLV) the proposed model is calibrate to human labels, the authors show .

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