Papers with low-resource regimes

2 papers
Enhancing Effectiveness and Robustness in a Low-Resource Regime via Decision-Boundary-aware Data Augmentation (2024.lrec-main)

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Challenge: Existing methods to augment textual data are limited due to the discrete characteristics of the textual dataset.
Approach: They propose a decision-boundary-aware data augmentation strategy to enhance robustness using pretrained language models by shifting latent features closer to the decision boundary and reconstruction to generate an ambiguous version with a soft label.
Outcome: The proposed method performs better than existing methods and is extensible with curriculum data augmentation.
PictoEduca: Building a Dataset for Spanish Text-to-Pictogram Generation (2026.findings-acl)

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Challenge: PictoEduca is the first large-scale Spanish text-to-pictogram dataset for augmentative and alternative communication.
Approach: They present PictoEduca, a large-scale Spanish text-to-pictogram dataset for augmentative and alternative communication.
Outcome: The proposed dataset combines automatic annotation with targeted expert correction, supporting scalable and high-quality corpus construction.

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