Papers by Jón Daðason

3 papers
Kvistur 2.0: a BiLSTM Compound Splitter for Icelandic (2020.lrec-1)

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Challenge: Compounding is highly productive in Icelandic, and new compounds are constantly being created.
Approach: They propose a character-based biLSTM model for splitting Icelandic compound words . the model learns how to split compound words into two parts .
Outcome: The proposed model outperforms other methods on a corpus of manually split word forms.
IceSum: An Icelandic Text Summarization Corpus (2021.naacl-srw)

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Challenge: Automatic Text Summarization (ATS) is the task of generating concise and fluent summaries from one or more documents.
Approach: They present a corpus of 1,000 Icelandic news articles and extractive summaries . they train several neural network-based models on the corpus and evaluate them .
Outcome: The proposed model outperforms baseline methods in the evaluation of the dataset and the models with an open license.
Text Filtering Classifiers for Medium-Resource Languages (2024.lrec-main)

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Challenge: linguistic and NLP researchers use web-crawled corpora to filter low-quality texts . early Transformer-based language models were typically pre-trained on curated corporum .
Approach: They compare the effectiveness of various text filtering classifiers on Icelandic, Estonian and Basque texts . they use a perplexity-based classifier and a self-supervised classifier trained on TQ-IS to discern between documents from curated and web-crawled corpora.
Outcome: The proposed classifiers achieve F1 scores of 94.48%, 99.01% and 93.40% on the Icelandic, Estonian and Basque datasets.

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