Papers by Jakub Pokrywka

2 papers
Challenging America: Modeling language in longer time scales (2022.findings-naacl)

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Challenge: a dominant approach to solving NLP tasks is pre-training a large neural language model and fine-tuning the model for specific tasks.
Approach: They propose a challenge to train and fine-tune large Transformer models for historical texts . they pre-trained a RoBERTa model from scratch from the historical texts and evaluate them on benchmarks .
Outcome: The proposed ML task is based on OCR-ed clippings from the Chronicling America portal.
Polish-English medical knowledge transfer: A new benchmark and results (2025.findings-emnlp)

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Challenge: Large Language Models have demonstrated significant potential in specialized tasks, including medical problem-solving.
Approach: They propose to use a Polish medical licensing and specialization exam dataset to evaluate LLMs . they use exam questions and parallel Polish-English corpora professionally translated for foreign candidates .
Outcome: The proposed dataset includes Polish exam questions and parallel Polish-English corpora professionally translated for foreign candidates.

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