Papers by Milán Konor Nyist

1 papers
From News to Summaries: Building a Hungarian Corpus for Extractive and Abstractive Summarization (2024.lrec-main)

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Challenge: Existing models and datasets for training summarization models are limited for less resourceful languages like Hungarian .
Approach: They propose to use a Hungarian corpus for training abstractive and extractive summarization models by cleaning, preprocessing and deduplication.
Outcome: The proposed model trains abstractive and extractive summarization models using the dataset . it will be made publicly available, encouraging replication, further research, and real-world applications across various domains.

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