Papers by Olia Toporkov

2 papers
Evaluating Shortest Edit Script Methods for Contextual Lemmatization (2024.lrec-main)

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Challenge: Modern contextual lemmatizers often rely on automatically induced Shortest Edit Scripts (SES) supervised contextual methods are used to perform lemma classification tasks.
Approach: They propose to use masked language encoders to compute shortest edit Scripts (SES) SES is the number of edit operations to transform a word form into its lemma .
Outcome: The proposed model outperforms language-specific models in all evaluation settings with seven languages of different morphological complexity.
Lemma Dilemma: On Lemma Generation Without Domain- or Language-Specific Training Data (2025.findings-emnlp)

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Challenge: Large language models (LLMs) can generate lemmas in context without prior fine-tuning.
Approach: They compare in-context lemma generation with traditional fully supervised approaches . they use encoder-only supervised methods and cross-lingual methods .
Outcome: The proposed model outperforms the traditional fully supervised approach in the context of lemmatization tasks.

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