AraFinNLP 2024: The First Arabic Financial NLP Shared Task
This addresses the problem of limited Arabic NLP resources for banking applications, but it is incremental as it builds on existing datasets and tasks.
The paper tackled the need for Arabic NLP tools in financial markets by organizing the AraFinNLP shared task with two subtasks on intent detection and translation, resulting in winning F1 and BLEU scores of 0.8773 and 1.667 respectively.
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.