HunSum-1 an abstractive summarization dataset for Hungarian /
We introduce HunSum-1 : a dataset for Hungarian abstractive summarization, consisting of 1.14M news articles. The dataset is built by collecting, cleaning and deduplicating data from 9 major Hungarian news sites through CommonCrawl. Using this dataset, we build abstractive summarizer models based on...
Elmentve itt :
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| Testületi szerző: | |
| Dokumentumtípus: | Könyv része |
| Megjelent: |
2023
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| Sorozat: | Magyar Számítógépes Nyelvészeti Konferencia
19 |
| Kulcsszavak: | Nyelvészet - számítógép alkalmazása |
| Tárgyszavak: | |
| Online Access: | http://acta.bibl.u-szeged.hu/78416 |
| Tartalmi kivonat: | We introduce HunSum-1 : a dataset for Hungarian abstractive summarization, consisting of 1.14M news articles. The dataset is built by collecting, cleaning and deduplicating data from 9 major Hungarian news sites through CommonCrawl. Using this dataset, we build abstractive summarizer models based on huBERT and mT5. We demonstrate the value of the created dataset by performing a quantitative and qualitative analysis on the models’ results. The HunSum-1 dataset, all models used in our experiments and our code1 are available open source. |
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| Terjedelem/Fizikai jellemzők: | 231-243 |
| ISBN: | 978-963-306-912-7 |