Papers with manual data curation

2 papers
Cross-lingual Text Classification Transfer: The Case of Ukrainian (2025.coling-main)

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Challenge: despite the large amount of labeled datasets, there is an imbalance in data availability across languages.
Approach: They explore cross-lingual knowledge transfer methods avoiding manual data curation . they use large multilingual encoders and translation systems, LLMs, and language adapters .
Outcome: The proposed approaches are tested on three text classification tasks in Ukrainian . the authors show that the proposed approaches avoid manual data curation .
TADPOLE: Task ADapted Pre-Training via AnOmaLy DEtection (2021.emnlp-main)

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Challenge: Existing approaches to solve domain shifts in NLP tasks require additional pre-training . current approaches focus on the downstream corpus when it is small, but are not effective .
Approach: They propose a task-adapted pre-training framework that can be used when the downstream corpus is too small for additional pre-tuning.
Outcome: The proposed framework outperforms baseline methods on biomedical, computer science, news, and movie reviews tasks.

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