AraFinNLP 2024: The First Arabic Financial NLP Shared Task

Sanad Malaysha, Mo El-Haj, Saad Ezzini, Mohammed Khalilia, Mustafa Jarrar +3 more
7/13/2024
cs.CL

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Abstract

The expanding financial markets of the Arab world require sophisticated Arabic NLP tools. To address this need within the banking domain, the Arabic Financial NLP (AraFinNLP) shared task proposes two subtasks: (i) Multi-dialect Intent Detection and (ii) Cross-dialect Translation and Intent Preservation. This shared task uses the updated ArBanking77 dataset, which includes about 39k parallel queries in MSA and four dialects. Each query is labeled with one or more of a common 77 intents in the banking domain. These resources aim to foster the development of robust financial Arabic NLP, particularly in the areas of machine translation and banking chat-bots. A total of 45 unique teams registered for this shared task, with 11 of them actively participated in the test phase. Specifically, 11 teams participated in Subtask 1, while only 1 team participated in Subtask 2. The winning team of Subtask 1 achieved F1 score of 0.8773, and the only team submitted in Subtask 2 achieved a 1.667 BLEU score.

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Cite this paper

@article{malaysha2024arafinnlp,
  title  = {AraFinNLP 2024: The First Arabic Financial NLP Shared Task},
  author = {Sanad Malaysha and Mo El-Haj and Saad Ezzini and Mohammed Khalilia and Mustafa Jarrar and Sultan Almujaiwel and Ismail Berrada and Houda Bouamor},
  year   = {2024},
  eprint = {2407.09818},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.09818v1}
}

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