Papers by Matej Klemen

2 papers
SENTA: Sentence Simplification System for Slovene (2024.lrec-main)

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Challenge: Sentence simplification involves converting complex sentences into more accessible forms while preserving their meaning and context.
Approach: They propose a system for sentence simplification in Slovene that uses a neural classifier to identify sentences that need simplification and a large Slovenen language model to refine sentences into a simpler form.
Outcome: The proposed system achieves an excellent SARI score of 41 for a large Slovene language model based on T5 architecture . it is integrated into a freely accessible, user-friendly user interface, offering a valuable service to less-fluent Slovenen users.
SI-NLI: A Slovene Natural Language Inference Dataset and Its Evaluation (2024.lrec-main)

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Challenge: Existing datasets for natural language inference (NLI) are limited to English and a few other well-resourced languages.
Approach: They propose to use a dataset for natural language inference to extend the resources for the task.
Outcome: The proposed dataset is constructed from scratch using knowledgeable annotators with carefully crafted guidelines aiming to avoid common problems in existing datasets.

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