Work

ELYADATA at NADI 2024 shared task: Arabic Dialect Identification with Similarity-Induced Mono-to-Multi Label Transformation.

Year: 2024

Type: conference-paper

Abstract: This paper describes our submissions to the Multi-label Country-level Dialect Identification subtask of the NADI2024 shared task, organized during the second edition of the Ara-bicNLP conference.Our submission is based on the ensemble of fine-tuned BERT-based models, after implementing the Similarity-Induced Mono-to-Multi Label Transformation (SIMMT) on the input data.Our submission ranked first with a Macro-Average F1 score of 50.57%.

Source: Arabic Natural Language Processing Workshop (WANLP)

DOI: 10.18653/v1/2024.arabicnlp-1.85

Authors: Amira Karoui, Farah Gharbi, Rami Kammoun, Imen Laouirine, Fethi Bougares

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4402671440

FWCI: 0.289

Cites:

Cited by: 1

Related to: 10