Papers by Krzysztof Jurkiewicz

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.
Oddballness: universal anomaly detection with language models (2025.coling-main)

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Challenge: a new method to detect anomalies in texts uses a metric called oddballness . the method considers probabilities generated by a language model but not low-likelihood tokens .
Approach: They propose a method to detect anomalies in texts using unsupervised language models . they define oddballness as a function that measures how strange a given token is .
Outcome: The proposed method is better than state-of-the-art models for grammatical error detection tasks.

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