Papers by Kirill Chirkunov
From Multiple-Choice to Extractive QA: A Case Study for English and Arabic (2025.coling-main)
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Teresa Lynn, Malik H. Altakrori, Samar M. Magdy, Rocktim Jyoti Das, Chenyang Lyu, Mohamed Nasr, Younes Samih, Kirill Chirkunov, Alham Fikri Aji, Preslav Nakov, Shantanu Godbole, Salim Roukos, Radu Florian, Nizar Habash
| Challenge: | Recent years have brought about very fast developments in Natural Language Processing (NLP), but many other languages are overlooked due to limited resources. |
| Approach: | They propose to repurpose a multilingual BELEBELE dataset for a task of extractive QA in the style of machine reading comprehension. |
| Outcome: | The proposed approach could be used to extract QA in the style of machine reading comprehension. |
Linear Semantic Segmentation for Low-Resource Spoken Dialects (2026.findings-acl)
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| Challenge: | Existing models for semantic segmentation are primarily developed and evaluated on high-resource written text, limiting their effectiveness on low-resourced conversational varieties. |
| Approach: | They propose a multi-genre benchmark for semantic segmentation in Arabic, focusing on dialectal discourse. |
| Outcome: | The proposed model outperforms baselines on dialectal non-news genres while performing well on high-resource written text. |