Papers by Mikołaj Koszowski

2 papers
Evaluation of Transfer Learning for Polish with a Text-to-Text Model (2022.lrec-1)

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Challenge: Recent years have brought significant progress in natural language understanding (NLU) and natural language generation (NLG).
Approach: They propose a benchmark for assessing the quality of text-to-text models for Polish . they evaluate the performance of plT5, mT5, Polish BART, and Polish GPT-2 .
Outcome: The proposed model can be fine-tuned on various NLP tasks with a single training objective.
ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT (2025.acl-short)

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Challenge: Neural Machine Translation (NMT) has improved translation by using Transformer-based models, but still struggles with word ambiguity and context.
Approach: They create a new Czech-to-polish e-commerce product translation dataset coupled with images and product metadata consisting of 11,400 sentence pairs.
Outcome: The proposed model incorporates visual cues alongside textual data to improve translation quality.

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