Work

Cher at KSAA-CAD 2024: Compressing Words and Definitions into the Same Space for Arabic Reverse Dictionary

Year: 2024

Type: conference-paper

Abstract: We present Team Cher's submission to the Ara-bicNLP 2024 KSAA-CAD shared task on the reverse dictionary for Arabic-the retrieval of words using definitions as a query.Our approach is based on a multi-task learning framework that jointly learns reverse dictionary, definition generation, and reconstruction tasks.This work explores different tokenization strategies and compares retrieval performance for each embedding architecture.Evaluation using the KSAA-CAD benchmark demonstrates the effectiveness of our multi-task approach and provides insights into the reverse dictionary task for Arabic.It is worth highlighting that we achieve strong performance without using any external resources in addition to the provided training data.

Source: Arabic Natural Language Processing Workshop (WANLP)

DOI: 10.18653/v1/2024.arabicnlp-1.75

Authors: Pinzhen Chen, Zheng Zhao, Shun Shao

Institutions: University of Edinburgh, University of Cambridge

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Government of the United Kingdom, UK Research and Innovation, HORIZON EUROPE Framework Programme

Award: G373773752