Papers by Julien Abadji
Towards a Cleaner Document-Oriented Multilingual Crawled Corpus (2022.lrec-1)
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| Challenge: | Existing web crawling pipelines are used to collect large corpora raw data, but the main way to collect such data is through manual data extraction. |
| Approach: | They propose to use a web crawler to extract and classify data from a multilingual web corpus and an automated annotation pipeline to improve it. |
| Outcome: | The proposed version of OSCAR could be used to pre-train large generative language models and other applications in Natural Language Processing and Digital Humanities. |
mOSCAR: A Large-scale Multilingual and Multimodal Document-level Corpus (2025.findings-acl)
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Matthieu Futeral, Armel Randy Zebaze, Pedro Ortiz Suarez, Julien Abadji, Rémi Lacroix, Cordelia Schmid, Rachel Bawden, Benoît Sagot
| Challenge: | Existing studies show that multimodal large language models can learn from text-image data. |
| Approach: | They propose to train multimodal large language models on large amounts of text-image data . they also show a boost in few-shot learning performance across various multilingual tasks . |
| Outcome: | The proposed dataset is not public and is only in English . it is the first large-scale multilingual and multimodal document corpus crawled from the web. |